mirror of
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53e73a7fda
Major improvements to period calculation with smarter defaults and simplified configuration: **Adaptive Defaults:** - ENABLE_MIN_PERIODS: true (was false) - Always try to find periods - MIN_PERIODS target: 2 periods/day (ensures coverage) - BEST_PRICE_MAX_LEVEL: "cheap" (was "any") - Prefer genuinely cheap - PEAK_PRICE_MIN_LEVEL: "expensive" (was "any") - Prefer genuinely expensive - GAP_TOLERANCE: 1 (was 0) - Allow 1-level deviations in sequences - MIN_DISTANCE_FROM_AVG: 5% (was 2%) - Ensure significance - PEAK_PRICE_MIN_PERIOD_LENGTH: 30min (was 60min) - More responsive - PEAK_PRICE_FLEX: -20% (was -15%) - Better peak detection **Volatility Filter Removal:** - Removed CONF_BEST_PRICE_MIN_VOLATILITY from const.py - Removed CONF_PEAK_PRICE_MIN_VOLATILITY from const.py - Removed volatility filter UI controls from config_flow.py - Removed filter_periods_by_volatility() calls from coordinator.py - Updated all 5 translations (de, en, nb, nl, sv) **Period Calculation Logic:** - Level filter now integrated into _build_periods() (applied during interval qualification, not as post-filter) - Gap tolerance implemented via _check_level_with_gap_tolerance() - Short periods (<1.5h) use strict filtering (no gap tolerance) - Relaxation now passes level_filter + gap_count directly to PeriodConfig - show_periods check skipped when relaxation enabled (relaxation tries "any" as fallback) **Documentation:** - Complete rewrite of docs/user/period-calculation.md: * Visual examples with timelines * Step-by-step explanation of 4-step process * Configuration scenarios (5 common use cases) * Troubleshooting section with specific fixes * Advanced topics (per-day independence, early stop, etc.) - Updated README.md: "volatility" → "distance from average" Impact: Periods now reliably appear on most days with meaningful quality filters. Users get warned about expensive periods and notified about cheap opportunities without manual tuning. Relaxation ensures coverage while keeping filters as strict as possible. Breaking change: Volatility filter removed (was never a critical feature, often confused users). Existing configs continue to work (removed keys are simply ignored).
2488 lines
73 KiB
Markdown
2488 lines
73 KiB
Markdown
# Period Calculation# Period Calculation# Period Calculation
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Learn how Best Price and Peak Price periods work, and how to configure them for your needs.
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## Table of ContentsLearn how Best Price and Peak Price periods work, and how to configure them for your needs.Learn how Best Price and Peak Price periods work, and how to configure them for your needs.
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- [Quick Start](#quick-start)
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- [How It Works](#how-it-works)
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- [Configuration Guide](#configuration-guide)## Table of Contents## Table of Contents
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- [Understanding Relaxation](#understanding-relaxation)
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- [Common Scenarios](#common-scenarios)
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- [Troubleshooting](#troubleshooting)
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- [Advanced Topics](#advanced-topics)- [Quick Start](#quick-start)- [Quick Start](#quick-start)
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---- [How It Works](#how-it-works)- [How It Works](#how-it-works)
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## Quick Start- [Configuration Guide](#configuration-guide)- [Configuration Guide](#configuration-guide)
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### What Are Price Periods?- [Understanding Relaxation](#understanding-relaxation)- [Understanding Relaxation](#understanding-relaxation)
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The integration finds time windows when electricity is especially **cheap** (Best Price) or **expensive** (Peak Price):- [Common Scenarios](#common-scenarios)- [Common Scenarios](#common-scenarios)
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- **Best Price Periods** 🟢 - When to run your dishwasher, charge your EV, or heat water- [Troubleshooting](#troubleshooting)- [Troubleshooting](#troubleshooting)
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- **Peak Price Periods** 🔴 - When to reduce consumption or defer non-essential loads
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- [Advanced Topics](#advanced-topics)- [Advanced Topics](#advanced-topics)
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### Default Behavior
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Out of the box, the integration:
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------
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1. **Best Price**: Finds cheapest 1-hour+ windows that are at least 5% below the daily average
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2. **Peak Price**: Finds most expensive 1-hour+ windows that are at least 5% above the daily average
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3. **Relaxation**: Automatically loosens filters if not enough periods are found
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## Quick Start## Quick Start
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### Example Timeline
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```
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00:00 ████████████████ Best Price Period (cheap prices)### What Are Price Periods?### What Are Price Periods?
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04:00 ░░░░░░░░░░░░░░░░ Normal
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08:00 ████████████████ Peak Price Period (expensive prices)
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12:00 ░░░░░░░░░░░░░░░░ Normal
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16:00 ████████████████ Peak Price Period (expensive prices)The integration finds time windows when electricity is especially **cheap** (Best Price) or **expensive** (Peak Price):The integration finds time windows when electricity is especially **cheap** (Best Price) or **expensive** (Peak Price):
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20:00 ████████████████ Best Price Period (cheap prices)
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```
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---- **Best Price Periods** 🟢 - When to run your dishwasher, charge your EV, or heat water- **Best Price Periods** 🟢 - When to run your dishwasher, charge your EV, or heat water
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## How It Works- **Peak Price Periods** 🔴 - When to reduce consumption or defer non-essential loads- **Peak Price Periods** 🔴 - When to reduce consumption or defer non-essential loads
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### The Four-Step Process
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#### 1. Find Extreme Prices### Default Behavior### Default Behavior
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First, identify the **minimum** (for Best Price) or **maximum** (for Peak Price) price of the day:
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```Out of the box, the integration:Out of the box, the integration:
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Daily prices: 18, 20, 22, 25, 23, 19, 17, 21 ct
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Minimum: 17 ct → Best Price anchor- ✅ Finds the cheapest time windows each day (Best Price)- ✅ Finds the cheapest time windows each day (Best Price)
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Maximum: 25 ct → Peak Price anchor
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```- ✅ Finds the most expensive time windows each day (Peak Price)- ✅ Finds the most expensive time windows each day (Peak Price)
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#### 2. Apply Flexibility- ✅ Requires periods to be at least 1 hour long- ✅ Requires periods to be at least 1 hour long
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Include intervals within a tolerance range of the extreme:- ✅ Automatically adjusts when no perfect matches exist (Relaxation)- ✅ Automatically adjusts when no perfect matches exist (Relaxation)
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**Best Price:**
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- Default: +15% above minimum
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- Example: 17 ct × 1.15 = 19.55 ct**Most users don't need to change anything!** The defaults work well for typical use cases.**Most users don't need to change anything!** The defaults work well for typical use cases.
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- Qualifying intervals: 17, 18, 19 ct ✓
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**Peak Price:**
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- Default: -15% below maximum (flex = -15%)------
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- Example: 25 ct × 0.85 = 21.25 ct
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- Qualifying intervals: 25, 23, 22 ct ✓
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#### 3. Apply Quality Filter (Min Distance)## How It Works## How It Works
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Ensure periods are **significantly** different from the daily average:
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```### The Basic Idea### The Basic Idea
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Daily average: 21 ct
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Minimum distance: 5% (default)
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Best Price threshold: 21 ct × 0.95 = 19.95 ctEach day, the integration analyzes all 96 quarter-hourly price intervals and identifies **continuous time ranges** that meet specific criteria.Each day, the integration analyzes all 96 quarter-hourly price intervals and identifies **continuous time ranges** that meet specific criteria.
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→ Periods must average below 19.95 ct
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Peak Price threshold: 21 ct × 1.05 = 22.05 ct
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→ Periods must average above 22.05 ctThink of it like this:Think of it like this:
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```
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1. **Find potential windows** - Times close to the daily MIN (Best Price) or MAX (Peak Price)1. **Find potential windows** - Times close to the daily MIN (Best Price) or MAX (Peak Price)
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#### 4. Apply Optional Filters
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2. **Filter by quality** - Ensure they're meaningfully different from average2. **Filter by quality** - Ensure they're meaningfully different from average
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You can optionally require:
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- **Absolute quality** (level filter) - "Only show if prices are CHEAP/EXPENSIVE (not just below/above average)"3. **Check duration** - Must be long enough to be useful3. **Check duration** - Must be long enough to be useful
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### Visual Example4. **Apply preferences** - Optional: only show stable prices, avoid mediocre times4. **Apply preferences** - Optional: only show stable prices, avoid mediocre times
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```
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Prices (ct/kWh):
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00:00 17 ████████████████ ← Minimum (anchor)### Step-by-Step Process### Step-by-Step Process
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01:00 18 █████████████████
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02:00 19 ██████████████████
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03:00 20 ███████████████████ ← Flexibility limit (17 × 1.15 = 19.55)
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04:00 22 █████████████████████#### 1. Define the Search Range (Flexibility)#### 1. Define the Search Range (Flexibility)
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05:00 25 ████████████████████████ ← Maximum
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06:00 21 ████████████████████ ← Daily average
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Best Price Period: 00:00-03:00 (17-19 ct, avg 18 ct)**Best Price:** How much MORE than the daily minimum can a price be?**Best Price:** How much MORE than the daily minimum can a price be?
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✓ Within flex (≤19.55 ct)
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✓ Below quality threshold (18 ct < 19.95 ct)``````
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✓ Long enough (3 hours ≥ 1 hour)
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```Daily MIN: 20 ct/kWhDaily MIN: 20 ct/kWh
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---Flexibility: 15% (default)Flexibility: 15% (default)
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## Configuration Guide→ Search for times ≤ 23 ct/kWh (20 + 15%)→ Search for times ≤ 23 ct/kWh (20 + 15%)
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### Core Parameters``````
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#### Minimum Period Length
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**What:** Shortest acceptable period duration**Peak Price:** How much LESS than the daily maximum can a price be?**Peak Price:** How much LESS than the daily maximum can a price be?
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**Default:** 60 minutes
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**Range:** 15-480 minutes``````
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```yamlDaily MAX: 40 ct/kWhDaily MAX: 40 ct/kWh
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best_price_min_period_length: 60 # At least 1 hour
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```Flexibility: -15% (default)Flexibility: -15% (default)
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**Use case:** Match appliance run times (dishwasher ECO: 180 min, quick wash: 60 min)→ Search for times ≥ 34 ct/kWh (40 - 15%)→ Search for times ≥ 34 ct/kWh (40 - 15%)
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#### Flexibility``````
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**What:** How far from the extreme price to search
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**Default:** 15% (Best Price), -15% (Peak Price)
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**Range:** 0-30%**Why flexibility?** Prices rarely stay at exactly MIN/MAX. Flexibility lets you capture realistic time windows.**Why flexibility?** Prices rarely stay at exactly MIN/MAX. Flexibility lets you capture realistic time windows.
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```yaml
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best_price_flex: 15 # Up to 15% above minimum
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peak_price_flex: -15 # Up to 15% below maximum#### 2. Ensure Quality (Distance from Average)#### 2. Ensure Quality (Distance from Average)
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```
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**Use case:**
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- **Tight** (5-10%): Only show truly extreme periodsPeriods must be meaningfully different from the daily average:Periods must be meaningfully different from the daily average:
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- **Relaxed** (20-30%): Show more opportunities
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#### Minimum Distance from Average
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``````
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**What:** How much better than average a period must be
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**Default:** 5%Daily AVG: 30 ct/kWhDaily AVG: 30 ct/kWh
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**Range:** 0-20%
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Minimum distance: 2% (default)Minimum distance: 2% (default)
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```yaml
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best_price_min_distance_from_avg: 5 # Must be 5% below average
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peak_price_min_distance_from_avg: 5 # Must be 5% above average
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```Best Price: Must be ≤ 29.4 ct/kWh (30 - 2%)Best Price: Must be ≤ 29.4 ct/kWh (30 - 2%)
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**Use case:**Peak Price: Must be ≥ 30.6 ct/kWh (30 + 2%)Peak Price: Must be ≥ 30.6 ct/kWh (30 + 2%)
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- **Strict** (5-10%): Only show significant opportunities
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- **Relaxed** (1-3%): Show more periods, even marginal ones``````
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### Optional Filters
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#### Level Filter (Absolute Quality)**Why?** This prevents marking mediocre times as "best" just because they're slightly below average.**Why?** This prevents marking mediocre times as "best" just because they're slightly below average.
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**What:** Only show periods with CHEAP/EXPENSIVE intervals (not just below/above average)
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**Default:** `any` (disabled)
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**Options:** `any` | `cheap` | `very_cheap` (Best Price) | `expensive` | `very_expensive` (Peak Price)#### 3. Check Duration#### 3. Check Duration
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```yaml
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best_price_max_level: any # Show any period below average
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best_price_max_level: cheap # Only show if at least one interval is CHEAPPeriods must be long enough to be practical:Periods must be long enough to be practical:
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```
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``````
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**Use case:** "Only notify me when prices are objectively cheap/expensive"
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Default: 60 minutes minimumDefault: 60 minutes minimum
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#### Gap Tolerance (for Level Filter)
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**What:** Allow N consecutive intervals that deviate by exactly one level step
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**Default:** 0 (strict filtering)45-minute period → Discarded45-minute period → Discarded
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**Range:** 0-5
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90-minute period → Kept ✓90-minute period → Kept ✓
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```yaml
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best_price_max_level_gap_count: 1 # Allow 1 NORMAL interval between CHEAP ones``````
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```
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**Use case:** Prevent periods from being split by occasional level deviations
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#### 4. Apply Optional Filters#### 4. Apply Optional Filters
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### Relaxation Settings
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#### Enable Relaxation
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You can optionally require:You can optionally require:
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**What:** Automatically loosen filters if not enough periods are found
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**Default:** Enabled- **Stable prices** (volatility filter) - "Only show if price doesn't fluctuate much"- **Stable prices** (volatility filter) - "Only show if price doesn't fluctuate much"
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```yaml- **Absolute quality** (level filter) - "Only show if prices are CHEAP/EXPENSIVE (not just below/above average)"- **Absolute quality** (level filter) - "Only show if prices are CHEAP/EXPENSIVE (not just below/above average)"
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enable_min_periods_best: true # Try to find at least min_periods
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min_periods_best: 1 # Target: 1 period per day
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```
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### Visual Example### Visual Example
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#### Relaxation Step Size
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**What:** How much to increase flexibility per relaxation phase
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**Default:** 25%**Timeline for a typical day:****Timeline for a typical day:**
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**Range:** 10-50%
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``````
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```yaml
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relaxation_step_best: 25 # Increase flex by 25% per phaseHour: 00 01 02 03 04 05 06 07 08 09 10 11 12 13 14 15 16 17 18 19 20 21 22 23Hour: 00 01 02 03 04 05 06 07 08 09 10 11 12 13 14 15 16 17 18 19 20 21 22 23
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```
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Price: 18 19 20 28 29 30 35 34 33 32 30 28 25 24 26 28 30 32 31 22 21 20 19 18Price: 18 19 20 28 29 30 35 34 33 32 30 28 25 24 26 28 30 32 31 22 21 20 19 18
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**Example:** With base flex 15% and step 25%:
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- Phase 1: 15% (original)
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- Phase 2: 18.75% (15% × 1.25)
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- Phase 3: 23.44% (18.75% × 1.25)Daily MIN: 18 ct | Daily MAX: 35 ct | Daily AVG: 26 ctDaily MIN: 18 ct | Daily MAX: 35 ct | Daily AVG: 26 ct
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- Phase 4: 29.3% (23.44% × 1.25)
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---
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Best Price (15% flex = ≤20.7 ct):Best Price (15% flex = ≤20.7 ct):
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## Understanding Relaxation
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████████ ████████████████ ████████ ████████████████
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### Why Relaxation?
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00:00-03:00 (3h) 19:00-24:00 (5h) 00:00-03:00 (3h) 19:00-24:00 (5h)
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Some days have unusual price patterns:
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- **Flat curves** (all prices very similar) → Hard to find periods significantly below/above average
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- **Missing extremes** (no CHEAP/EXPENSIVE intervals) → Level filters block everything
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- **Short cheap windows** (only 15-30 min blocks) → Can't meet minimum lengthPeak Price (-15% flex = ≥29.75 ct):Peak Price (-15% flex = ≥29.75 ct):
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Relaxation ensures you still get notified about the best opportunities available, even on difficult days. ████████████████████████ ████████████████████████
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### The 4×3 Relaxation Matrix 06:00-11:00 (5h) 06:00-11:00 (5h)
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When enabled, relaxation tries **4 flexibility levels** × **3 filter combinations** = 12 strategies:``````
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#### 4 Flexibility Levels:
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1. Original (e.g., 15%)
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2. Step 1 (e.g., 18.75%)------
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3. Step 2 (e.g., 23.44%)
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4. Step 3 (e.g., 29.3%)
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#### 3 Filter Combinations (per flexibility level):## Configuration Guide## Configuration Guide
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1. **Original filters** (flex + min_distance + level_filter)
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2. **Remove level filter** (flex + min_distance + level_override=any)
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3. **Remove both** (flex + level_override=any + min_distance_override=0%)
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### Basic Settings### Basic Settings
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### Relaxation Flow
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```
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Start: Flex 15% + min_distance 5% + level CHEAP#### Flexibility#### Flexibility
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Phase 1: Flex 15.0% + Original filters → Not enough periods
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Phase 2: Flex 15.0% + Level=any → Not enough periods
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Phase 3: Flex 15.0% + All filters off → Not enough periods**What:** How far from MIN/MAX to search for periods **What:** How far from MIN/MAX to search for periods
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Phase 4: Flex 18.75% + Original filters → Not enough periods**Default:** 15% (Best Price), -15% (Peak Price) **Default:** 15% (Best Price), -15% (Peak Price)
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Phase 5: Flex 18.75% + Level=any → SUCCESS! Found 2 periods ✓
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→ Stop early (no need to try higher flex)**Range:** 0-100%**Range:** 0-100%
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```
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### Tracking Relaxation
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```yaml```yaml
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The integration tracks which filters were applied via the `relaxation_level` attribute:
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best_price_flex: 15 # Can be up to 15% more expensive than daily MINbest_price_flex: 15 # Can be up to 15% more expensive than daily MIN
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```yaml
|
||
|
||
relaxation_level: "flex_18.75_level_any"peak_price_flex: -15 # Can be up to 15% less expensive than daily MAXpeak_price_flex: -15 # Can be up to 15% less expensive than daily MAX
|
||
|
||
```
|
||
|
||
``````
|
||
|
||
**Possible values:**
|
||
|
||
- `none` - Original filters worked
|
||
|
||
- `flex_X.XX` - Increased flexibility (X.XX%)
|
||
|
||
- `flex_X.XX_level_any` - Increased flex + disabled level filter**When to adjust:****When to adjust:**
|
||
|
||
- `flex_X.XX_all_off` - Increased flex + all filters disabled
|
||
|
||
- **Increase (20-25%)** → Find more/longer periods- **Increase (20-25%)** → Find more/longer periods
|
||
|
||
---
|
||
|
||
- **Decrease (5-10%)** → Find only the very best/worst times- **Decrease (5-10%)** → Find only the very best/worst times
|
||
|
||
## Common Scenarios
|
||
|
||
|
||
|
||
### Scenario 1: Simple Best Price (Default)
|
||
|
||
#### Minimum Period Length#### Minimum Period Length
|
||
|
||
**Goal:** Find cheapest 1-hour windows
|
||
|
||
|
||
|
||
```yaml
|
||
|
||
best_price_min_period_length: 60**What:** How long a period must be to show it **What:** How long a period must be to show it
|
||
|
||
best_price_flex: 15
|
||
|
||
best_price_min_distance_from_avg: 5 # (default)**Default:** 60 minutes **Default:** 60 minutes
|
||
|
||
best_price_max_level: any
|
||
|
||
enable_min_periods_best: true**Range:** 15-240 minutes**Range:** 15-240 minutes
|
||
|
||
```
|
||
|
||
|
||
|
||
**Result:** Finds any 1-hour+ period with prices ≤15% above minimum AND ≥5% below daily average.
|
||
|
||
```yaml```yaml
|
||
|
||
### Scenario 2: Strict Best Price (Only Objectively Cheap)
|
||
|
||
best_price_min_period_length: 60best_price_min_period_length: 60
|
||
|
||
**Goal:** Only show best price when prices are truly CHEAP
|
||
|
||
peak_price_min_period_length: 60peak_price_min_period_length: 60
|
||
|
||
```yaml
|
||
|
||
best_price_min_period_length: 60``````
|
||
|
||
best_price_flex: 10 # Tighter tolerance
|
||
|
||
best_price_min_distance_from_avg: 8 # Much better than average
|
||
|
||
best_price_max_level: cheap # Must have CHEAP intervals
|
||
|
||
best_price_max_level_gap_count: 1 # Allow 1 gap**When to adjust:****When to adjust:**
|
||
|
||
enable_min_periods_best: true
|
||
|
||
```- **Increase (90-120 min)** → Only show longer periods (e.g., for heat pump cycles)- **Increase (90-120 min)** → Only show longer periods (e.g., for heat pump cycles)
|
||
|
||
|
||
|
||
**Result:** Very selective - only shows periods that are significantly and objectively cheap.- **Decrease (30-45 min)** → Show shorter windows (e.g., for quick tasks)- **Decrease (30-45 min)** → Show shorter windows (e.g., for quick tasks)
|
||
|
||
|
||
|
||
### Scenario 3: Relaxed Best Price (More Opportunities)
|
||
|
||
|
||
|
||
**Goal:** Show more best price periods, even marginal ones#### Distance from Average#### Distance from Average
|
||
|
||
|
||
|
||
```yaml
|
||
|
||
best_price_min_period_length: 45 # Shorter periods OK
|
||
|
||
best_price_flex: 25 # Wider tolerance**What:** How much better than average a period must be **What:** How much better than average a period must be
|
||
|
||
best_price_min_distance_from_avg: 2 # Less strict
|
||
|
||
best_price_max_level: any**Default:** 2% **Default:** 2%
|
||
|
||
enable_min_periods_best: true
|
||
|
||
```**Range:** 0-20%**Range:** 0-20%
|
||
|
||
|
||
|
||
**Result:** Shows more periods, including those only slightly cheaper than average.
|
||
|
||
|
||
|
||
### Scenario 4: Peak Price Warning (Avoid Expensive Times)```yaml```yaml
|
||
|
||
|
||
|
||
**Goal:** Get warned about expensive periodsbest_price_min_distance_from_avg: 2best_price_min_distance_from_avg: 2
|
||
|
||
|
||
|
||
```yamlpeak_price_min_distance_from_avg: 2peak_price_min_distance_from_avg: 2
|
||
|
||
peak_price_min_period_length: 60
|
||
|
||
peak_price_flex: -15``````
|
||
|
||
peak_price_min_distance_from_avg: 5
|
||
|
||
peak_price_min_level: expensive # Must be objectively expensive
|
||
|
||
enable_min_periods_peak: true
|
||
|
||
```**When to adjust:****When to adjust:**
|
||
|
||
|
||
|
||
**Result:** Shows peak prices only when they're significantly above average AND contain EXPENSIVE intervals.- **Increase (5-10%)** → Only show clearly better times- **Increase (5-10%)** → Only show clearly better times
|
||
|
||
|
||
|
||
### Scenario 5: Match Long Appliance Cycle- **Decrease (0-1%)** → Show any time below/above average- **Decrease (0-1%)** → Show any time below/above average
|
||
|
||
|
||
|
||
**Goal:** Find 3-hour window for slow dishwasher ECO program
|
||
|
||
|
||
|
||
```yaml### Optional Filters### Optional Filters
|
||
|
||
best_price_min_period_length: 180 # 3 hours minimum
|
||
|
||
best_price_flex: 20 # More flexibility to find longer periods
|
||
|
||
best_price_min_distance_from_avg: 5
|
||
|
||
enable_min_periods_best: true#### Volatility Filter (Price Stability)#### Volatility Filter (Price Stability)
|
||
|
||
```
|
||
|
||
|
||
|
||
**Result:** Finds 3+ hour windows, may relax flexibility if needed.
|
||
|
||
**What:** Only show periods with stable prices (low fluctuation) **What:** Only show periods with stable prices (low fluctuation)
|
||
|
||
---
|
||
|
||
**Default:** `low` (disabled) **Default:** `low` (disabled)
|
||
|
||
## Troubleshooting
|
||
|
||
**Options:** `low` | `moderate` | `high` | `very_high`**Options:** `low` | `moderate` | `high` | `very_high`
|
||
|
||
### No Periods Found
|
||
|
||
|
||
|
||
**Symptom:** `binary_sensor.tibber_home_best_price_period` never turns "on"
|
||
|
||
```yaml```yaml
|
||
|
||
**Possible causes:**
|
||
|
||
best_price_min_volatility: low # Show all periodsbest_price_min_volatility: low # Show all periods
|
||
|
||
1. **Filters too strict**
|
||
|
||
best_price_min_volatility: moderate # Only show if price doesn't swing >5 ctbest_price_min_volatility: moderate # Only show if price doesn't swing >5 ct
|
||
|
||
```yaml
|
||
|
||
# Try:``````
|
||
|
||
best_price_flex: 20 # Increase from default 15%
|
||
|
||
best_price_min_distance_from_avg: 2 # Reduce from default 5%
|
||
|
||
```
|
||
|
||
**Use case:** "I want predictable prices during the period"**Use case:** "I want predictable prices during the period"
|
||
|
||
2. **Period length too long**
|
||
|
||
|
||
|
||
```yaml
|
||
|
||
# Try:#### Level Filter (Absolute Quality)#### Level Filter (Absolute Quality)
|
||
|
||
best_price_min_period_length: 45 # Reduce from 60 minutes
|
||
|
||
```
|
||
|
||
|
||
|
||
3. **Flat price curve** (all prices very similar)**What:** Only show periods with CHEAP/EXPENSIVE intervals (not just below/above average) **What:** Only show periods with CHEAP/EXPENSIVE intervals (not just below/above average)
|
||
|
||
|
||
|
||
Solution: Enable relaxation (should be default)**Default:** `any` (disabled) **Default:** `any` (disabled)
|
||
|
||
```yaml
|
||
|
||
enable_min_periods_best: true**Options:** `any` | `cheap` | `very_cheap` (Best Price) | `expensive` | `very_expensive` (Peak Price)**Options:** `any` | `cheap` | `very_cheap` (Best Price) | `expensive` | `very_expensive` (Peak Price)
|
||
|
||
```
|
||
|
||
|
||
|
||
4. **Level filter too strict**
|
||
|
||
```yaml```yaml
|
||
|
||
```yaml
|
||
|
||
# Try:best_price_max_level: any # Show any period below averagebest_price_max_level: any # Show any period below average
|
||
|
||
best_price_max_level: any # Disable level filter
|
||
|
||
```best_price_max_level: cheap # Only show if at least one interval is CHEAPbest_price_max_level: cheap # Only show if at least one interval is CHEAP
|
||
|
||
|
||
|
||
### Too Many Periods``````
|
||
|
||
|
||
|
||
**Symptom:** Best price is "on" most of the day
|
||
|
||
|
||
|
||
**Solution:** Make filters stricter**Use case:** "Only notify me when prices are objectively cheap/expensive"**Use case:** "Only notify me when prices are objectively cheap/expensive"
|
||
|
||
|
||
|
||
```yaml
|
||
|
||
best_price_flex: 10 # Reduce from default 15%
|
||
|
||
best_price_min_distance_from_avg: 8 # Increase from default 5%#### Gap Tolerance (for Level Filter)#### Gap Tolerance (for Level Filter)
|
||
|
||
best_price_max_level: cheap # Require CHEAP intervals
|
||
|
||
```
|
||
|
||
|
||
|
||
### Periods Too Short**What:** Allow some "mediocre" intervals within an otherwise good period **What:** Allow some "mediocre" intervals within an otherwise good period
|
||
|
||
|
||
|
||
**Symptom:** Best price periods are only 15-30 minutes**Default:** 0 (strict) **Default:** 0 (strict)
|
||
|
||
|
||
|
||
**Solution:****Range:** 0-10**Range:** 0-10
|
||
|
||
|
||
|
||
```yaml
|
||
|
||
best_price_min_period_length: 90 # Increase minimum length
|
||
|
||
``````yaml```yaml
|
||
|
||
|
||
|
||
### Wrong Level Filter Resultsbest_price_max_level: cheapbest_price_max_level: cheap
|
||
|
||
|
||
|
||
**Symptom:** Period shows even though no CHEAP intervals existbest_price_max_level_gap_count: 2 # Allow up to 2 NORMAL intervals per periodbest_price_max_level_gap_count: 2 # Allow up to 2 NORMAL intervals per period
|
||
|
||
|
||
|
||
**Check:**``````
|
||
|
||
1. Look at `relaxation_level` attribute - is it `level_any`?
|
||
|
||
2. If yes, relaxation disabled the level filter because no periods were found
|
||
|
||
3. Solution: Disable relaxation or increase target periods
|
||
|
||
**Use case:** "Don't split periods just because one interval isn't perfectly CHEAP"**Use case:** "Don't split periods just because one interval isn't perfectly CHEAP"
|
||
|
||
```yaml
|
||
|
||
enable_min_periods_best: false # Strict mode
|
||
|
||
# OR
|
||
|
||
min_periods_best: 2 # Try harder to keep filters------
|
||
|
||
```
|
||
|
||
|
||
|
||
---
|
||
|
||
## Understanding Relaxation## Understanding Relaxation
|
||
|
||
## Advanced Topics
|
||
|
||
|
||
|
||
### Per-Day Independence
|
||
|
||
### What Is Relaxation?### What Is Relaxation?
|
||
|
||
**Important:** Relaxation operates **independently per day**. Each day (today/tomorrow) has its own relaxation state.
|
||
|
||
|
||
|
||
**Example:**
|
||
|
||
```yamlSometimes, strict filters find too few periods (or none). **Relaxation automatically loosens filters** until a minimum number of periods is found.Sometimes, strict filters find too few periods (or none). **Relaxation automatically loosens filters** until a minimum number of periods is found.
|
||
|
||
# 2025-11-11 (today):
|
||
|
||
Baseline: Found 2 periods → SUCCESS (no relaxation)
|
||
|
||
relaxation_level: "none"
|
||
|
||
### How to Enable### How to Enable
|
||
|
||
# 2025-11-12 (tomorrow):
|
||
|
||
Baseline: Found 0 periods → Start relaxation
|
||
|
||
Phase 1: flex 18.75% → Found 1 period → PARTIAL
|
||
|
||
Phase 2: flex 23.44% + level=any → Found 2 periods → SUCCESS```yaml```yaml
|
||
|
||
relaxation_level: "flex_23.44_level_any"
|
||
|
||
```enable_min_periods_best: trueenable_min_periods_best: true
|
||
|
||
|
||
|
||
This ensures that:min_periods_best: 2 # Try to find at least 2 periods per daymin_periods_best: 2 # Try to find at least 2 periods per day
|
||
|
||
- Good days keep strict filters
|
||
|
||
- Difficult days get helprelaxation_step_best: 35 # Increase flex by 35% per step (e.g., 15% → 20.25% → 27.3%)relaxation_step_best: 35 # Increase flex by 35% per step (e.g., 15% → 20.25% → 27.3%)
|
||
|
||
- Each day is evaluated fairly
|
||
|
||
``````
|
||
|
||
### Period Merging and Replacement
|
||
|
||
|
||
|
||
When building periods, the algorithm:
|
||
|
||
### How It Works (Smart 4×4 Matrix)### How It Works (New Smart Strategy)
|
||
|
||
1. **Merges adjacent qualifying intervals** into continuous periods
|
||
|
||
2. **Replaces smaller periods** with larger overlapping ones```
|
||
|
||
|
||
|
||
**Example:**Relaxation uses a **4×4 matrix approach** - trying 4 flexibility levels with 4 different filter combinations (16 attempts total per day):Found periods:
|
||
|
||
```
|
||
|
||
Baseline finds: 00:00-01:00 (1h), 00:30-01:30 (1h)- 00:00-01:00 (60 min) ✓ Keep
|
||
|
||
→ Larger period (00:30-01:30) replaces smaller one (00:00-01:00)
|
||
|
||
→ Result: Single period 00:30-01:30#### Phase Matrix- 03:00-03:30 (30 min) ✗ Discard (too short)
|
||
|
||
|
||
|
||
Relaxation adds: 00:15-01:45 (1.5h)- 14:00-15:15 (75 min) ✓ Keep
|
||
|
||
→ Even larger period replaces previous
|
||
|
||
→ Result: Single period 00:15-01:45For each day, the system tries:```
|
||
|
||
```
|
||
|
||
|
||
|
||
This prevents overlapping periods and ensures you get the **longest possible cheap/expensive window**.
|
||
|
||
**4 Flexibility Levels:**
|
||
|
||
### Early Stop Optimization
|
||
|
||
1. Original (e.g., 15%)### How It Works (New Smart Strategy)
|
||
|
||
Relaxation stops as soon as the target period count is reached:
|
||
|
||
2. +35% step (e.g., 20.25%)
|
||
|
||
```
|
||
|
||
Target: 2 periods3. +35% step (e.g., 27.3%)Relaxation uses a **4×4 matrix approach** - trying 4 flexibility levels with 4 different filter combinations (16 attempts total per day):
|
||
|
||
|
||
|
||
Phase 1: Flex 15.0% + Original → 0 periods4. +35% step (e.g., 36.9%)
|
||
|
||
Phase 2: Flex 15.0% + Level=any → 1 period (partial)
|
||
|
||
Phase 3: Flex 15.0% + All off → 2 periods ✓ STOP#### Phase Matrix
|
||
|
||
|
||
|
||
No need to try flex 18.75%, 23.44%, 29.3%!**4 Filter Combinations (per flexibility level):**
|
||
|
||
```
|
||
|
||
1. Original filters (your configured volatility + level)For each day, the system tries:
|
||
|
||
This:
|
||
|
||
- Keeps filters as strict as possible2. Remove volatility filter (keep level filter)
|
||
|
||
- Reduces computation time
|
||
|
||
- Provides predictable behavior3. Remove level filter (keep volatility filter)**4 Flexibility Levels:**
|
||
|
||
|
||
|
||
### Volatility Information (Not a Filter)4. Remove both filters1. Original (e.g., 15%)
|
||
|
||
|
||
|
||
**Important:** Volatility is **NOT** used as a filter. It's calculated as an **information attribute** for each period:2. +35% step (e.g., 20.25%)
|
||
|
||
|
||
|
||
```yaml**Example progression:**3. +35% step (e.g., 27.3%)
|
||
|
||
attributes:
|
||
|
||
volatility: "LOW" # Info only```4. +35% step (e.g., 36.9%)
|
||
|
||
volatility_numeric: 2.3 # Spread in ct/kWh
|
||
|
||
```Flex 15% + Original filters → Not enough periods
|
||
|
||
|
||
|
||
**Volatility levels:**Flex 15% + Volatility=any → Not enough periods**4 Filter Combinations (per flexibility level):**
|
||
|
||
- `LOW`: Spread < 5 ct (stable prices)
|
||
|
||
- `MODERATE`: 5 ≤ spread < 15 ctFlex 15% + Level=any → Not enough periods1. Original filters (your configured volatility + level)
|
||
|
||
- `HIGH`: 15 ≤ spread < 30 ct
|
||
|
||
- `VERY_HIGH`: spread ≥ 30 ctFlex 15% + All filters off → Not enough periods2. Remove volatility filter (keep level filter)
|
||
|
||
|
||
|
||
**Use case:** You can use this information in automations, but it doesn't affect which periods are found.Flex 20.25% + Original → SUCCESS! Found 2 periods ✓3. Remove level filter (keep volatility filter)
|
||
|
||
|
||
|
||
### Level Filter Implementation(stops here - no need to try more)4. Remove both filters
|
||
|
||
|
||
|
||
The level filter applies **during interval qualification**, not as a post-filter:```
|
||
|
||
|
||
|
||
```python**Example progression:**
|
||
|
||
# Simplified logic
|
||
|
||
for interval in all_intervals:#### Per-Day Independence```
|
||
|
||
in_flex = check_flexibility(interval, extreme)
|
||
|
||
meets_min_distance = check_min_distance(interval, average)Flex 15% + Original filters → Not enough periods
|
||
|
||
meets_level = check_level(interval, level_filter) # Applied here
|
||
|
||
**Critical:** Each day relaxes **independently**:Flex 15% + Volatility=any → Not enough periods
|
||
|
||
if in_flex and meets_min_distance and meets_level:
|
||
|
||
add_to_candidates(interval)Flex 15% + Level=any → Not enough periods
|
||
|
||
```
|
||
|
||
```Flex 15% + All filters off → Not enough periods
|
||
|
||
This means:
|
||
|
||
- Intervals are filtered **before** period buildingDay 1: Finds 2 periods with flex 15% (original) → No relaxation neededFlex 20.25% + Original → SUCCESS! Found 2 periods ✓
|
||
|
||
- Gap tolerance prevents splitting during period construction
|
||
|
||
- More efficient than filtering complete periodsDay 2: Needs flex 27.3% + level=any → Uses relaxed settings(stops here - no need to try more)
|
||
|
||
|
||
|
||
### Configuration PersistenceDay 3: Finds 2 periods with flex 15% (original) → No relaxation needed```
|
||
|
||
|
||
|
||
Period configuration is stored in Home Assistant's config entry options and persists across restarts. Changes take effect immediately without restarting HA.```
|
||
|
||
|
||
|
||
---#### Per-Day Independence
|
||
|
||
|
||
|
||
## Quick Reference**Why?** Price patterns vary daily. Some days have clear cheap/expensive windows (strict filters work), others don't (relaxation needed).
|
||
|
||
|
||
|
||
### Parameter Summary (Best Price)**Critical:** Each day relaxes **independently**:
|
||
|
||
|
||
|
||
| Parameter | Default | Range | Purpose |#### Period Replacement Logic
|
||
|
||
|-----------|---------|-------|---------|
|
||
|
||
| `best_price_min_period_length` | 60 min | 15-480 min | Minimum duration |```
|
||
|
||
| `best_price_flex` | 15% | 0-30% | Tolerance above min |
|
||
|
||
| `best_price_min_distance_from_avg` | 5% | 0-20% | Quality threshold |When relaxation finds new periods, they interact with baseline periods in two ways:Day 1: Finds 2 periods with flex 15% (original) → No relaxation needed
|
||
|
||
| `best_price_max_level` | any | any/cheap/very_cheap | Level filter |
|
||
|
||
| `best_price_max_level_gap_count` | 0 | 0-5 | Gap tolerance |Day 2: Needs flex 27.3% + level=any → Uses relaxed settings
|
||
|
||
| `enable_min_periods_best` | true | true/false | Enable relaxation |
|
||
|
||
| `min_periods_best` | 1 | 1-5 | Target periods |**1. Extension** (Enlargement)Day 3: Finds 2 periods with flex 15% (original) → No relaxation needed
|
||
|
||
| `relaxation_step_best` | 25% | 10-50% | Flex increase step |
|
||
|
||
A relaxed period that **overlaps** with a baseline period and extends it:```
|
||
|
||
**Peak Price:** Same parameters with `peak_price_*` prefix (defaults: flex=-15%, level options: expensive/very_expensive)
|
||
|
||
```
|
||
|
||
### Filter Priority (Order of Application)
|
||
|
||
Baseline: [14:00-16:00] ████████**Why?** Price patterns vary daily. Some days have clear cheap/expensive windows (strict filters work), others don't (relaxation needed).
|
||
|
||
1. **Flexibility** - Within X% of extreme (REQUIRED)
|
||
|
||
2. **Level Filter** - Must have CHEAP/EXPENSIVE intervals (OPTIONAL)Relaxed: [13:00-16:30] ████████████
|
||
|
||
3. **Gap Tolerance** - Allow N deviating intervals (with level filter only)
|
||
|
||
4. **Min Distance** - Must be X% better than average (REQUIRED)Result: [13:00-16:30] ████████████████ (baseline expanded)#### Period Replacement Logic
|
||
|
||
5. **Min Length** - Period must be ≥X minutes (REQUIRED)
|
||
|
||
↑ Keeps baseline metadata (original flex/filters)
|
||
|
||
### Relaxation Priority (Order of Loosening)
|
||
|
||
```When relaxation finds new periods, they interact with baseline periods in two ways:
|
||
|
||
1. Keep all filters, increase flex
|
||
|
||
2. Disable level filter, keep min_distance
|
||
|
||
3. Disable both level and min_distance filters
|
||
|
||
**2. Replacement** (Substitution)**1. Extension** (Enlargement)
|
||
|
||
---
|
||
|
||
A **larger** relaxed period completely contains a **smaller** relaxed period from earlier phases:A relaxed period that **overlaps** with a baseline period and extends it:
|
||
|
||
## Related Documentation
|
||
|
||
``````
|
||
|
||
- **[Configuration Guide](configuration.md)** - Full integration setup
|
||
|
||
- **[Sensors Reference](sensors.md)** - All available sensorsPhase 1: [14:00-15:00] ████ (found with flex 15%)Baseline: [14:00-16:00] ████████
|
||
|
||
- **[Automation Examples](automation-examples.md)** - Ready-to-use automations
|
||
|
||
- **[Troubleshooting](troubleshooting.md)** - Common issues and solutionsPhase 3: [13:00-17:00] ████████████ (found with flex 27.3%)Relaxed: [13:00-16:30] ████████████
|
||
|
||
|
||
Result: [13:00-17:00] ████████████ (larger replaces smaller)Result: [13:00-16:30] ████████████████ (baseline expanded)
|
||
|
||
↑ Uses Phase 3 metadata (flex 27.3%) ↑ Keeps baseline metadata (original flex/filters)
|
||
|
||
``````
|
||
|
||
|
||
|
||
**Why two different behaviors?****2. Replacement** (Substitution)
|
||
|
||
- **Extensions preserve quality:** Baseline periods found with original strict filters are high-quality. When relaxation finds overlapping periods, we expand the baseline but keep its original metadata (indicating it was found with strict criteria).A **larger** relaxed period completely contains a **smaller** relaxed period from earlier phases:
|
||
|
||
- **Replacements reflect reality:** When a larger relaxed period is found, it completely replaces smaller relaxed periods because it better represents the actual price window. The metadata shows which relaxation phase actually found this period.```
|
||
|
||
Phase 1: [14:00-15:00] ████ (found with flex 15%)
|
||
|
||
**Key principle:** Baseline periods are "gold standard" - they get extended but never replaced. Relaxed periods compete with each other based on size.Phase 3: [13:00-17:00] ████████████ (found with flex 27.3%)
|
||
|
||
Result: [13:00-17:00] ████████████ (larger replaces smaller)
|
||
|
||
#### Counting Logic ↑ Uses Phase 3 metadata (flex 27.3%)
|
||
|
||
```
|
||
|
||
The system counts **standalone periods** (periods that remain in the final result):
|
||
|
||
**Why two different behaviors?**
|
||
|
||
```- **Extensions preserve quality:** Baseline periods found with original strict filters are high-quality. When relaxation finds overlapping periods, we expand the baseline but keep its original metadata (indicating it was found with strict criteria).
|
||
|
||
After all relaxation phases:- **Replacements reflect reality:** When a larger relaxed period is found, it completely replaces smaller relaxed periods because it better represents the actual price window. The metadata shows which relaxation phase actually found this period.
|
||
|
||
- Period A: Extended baseline (counts ✓)
|
||
|
||
- Period B: Standalone relaxed (counts ✓)**Key principle:** Baseline periods are "gold standard" - they get extended but never replaced. Relaxed periods compete with each other based on size.
|
||
|
||
- Period C: Was replaced by larger period (doesn't count ✗)
|
||
|
||
#### Counting Logic
|
||
|
||
Total: 2 periods
|
||
|
||
Comparison: ≥ min_periods_best? → Yes → SUCCESSThe system counts **standalone periods** (periods that remain in the final result):
|
||
|
||
```
|
||
|
||
```
|
||
|
||
### Metadata TrackingAfter all relaxation phases:
|
||
|
||
- Period A: Extended baseline (counts ✓)
|
||
|
||
Each period shows **how it was found** via entity attributes:- Period B: Standalone relaxed (counts ✓)
|
||
|
||
- Period C: Was replaced by larger period (doesn't count ✗)
|
||
|
||
**Baseline Period (no relaxation needed):**
|
||
|
||
```yamlTotal: 2 periods
|
||
|
||
relaxation_active: falseComparison: ≥ min_periods_best? → Yes → SUCCESS
|
||
|
||
relaxation_level: "price_diff_15.0%" # Original flexibility```
|
||
|
||
```
|
||
|
||
### Metadata Tracking
|
||
|
||
**Extended Baseline (relaxation extended it):**
|
||
|
||
```yamlEach period shows **how it was found** via entity attributes:
|
||
|
||
relaxation_active: true # Relaxation was needed globally
|
||
|
||
relaxation_level: "price_diff_15.0%" # But THIS period was baseline**Baseline Period (no relaxation needed):**
|
||
|
||
``````yaml
|
||
|
||
relaxation_active: false
|
||
|
||
**Standalone Relaxed Period:**relaxation_level: "price_diff_15.0%" # Original flexibility
|
||
|
||
```yaml```
|
||
|
||
relaxation_active: true
|
||
|
||
relaxation_level: "price_diff_27.3%+level_any" # Found at flex 27.3%, level filter removed**Extended Baseline (relaxation extended it):**
|
||
|
||
``````yaml
|
||
|
||
relaxation_active: true # Relaxation was needed globally
|
||
|
||
**Replaced Period (doesn't appear in final result):**relaxation_level: "price_diff_15.0%" # But THIS period was baseline
|
||
|
||
- Not exposed as entity (was replaced by larger period)```
|
||
|
||
|
||
|
||
### Configuration Example**Standalone Relaxed Period:**
|
||
|
||
```yaml
|
||
|
||
```yamlrelaxation_active: true
|
||
|
||
# Best Price with relaxationrelaxation_level: "price_diff_27.3%+level_any" # Found at flex 27.3%, level filter removed
|
||
|
||
enable_min_periods_best: true```
|
||
|
||
min_periods_best: 2 # Try to find at least 2 periods per day
|
||
|
||
relaxation_step_best: 35 # Increase flex by 35% per step**Replaced Period (doesn't appear in final result):**
|
||
|
||
best_price_flex: 15 # Start with 15%- Not exposed as entity (was replaced by larger period)
|
||
|
||
best_price_min_volatility: moderate # Start with volatility filter
|
||
|
||
best_price_max_level: cheap # Start with level filter### Configuration Example
|
||
|
||
|
||
|
||
# Result: Tries up to 16 combinations per day:```yaml
|
||
|
||
# Flex 15%/20.25%/27.3%/36.9% × Filters original/vol-any/lvl-any/all-any# Best Price with relaxation
|
||
|
||
# Stops immediately when 2 periods foundenable_min_periods_best: true
|
||
|
||
```min_periods_best: 2 # Try to find at least 2 periods per day
|
||
|
||
relaxation_step_best: 35 # Increase flex by 35% per step
|
||
|
||
---best_price_flex: 15 # Start with 15%
|
||
|
||
best_price_min_volatility: moderate # Start with volatility filter
|
||
|
||
## Common Scenariosbest_price_max_level: cheap # Start with level filter
|
||
|
||
|
||
|
||
### Scenario 1: Simple Best Price (Default)# Result: Tries up to 16 combinations per day:
|
||
|
||
# Flex 15%/20.25%/27.3%/36.9% × Filters original/vol-any/lvl-any/all-any
|
||
|
||
**Goal:** Find the cheapest time each day to run dishwasher# Stops immediately when 2 periods found
|
||
|
||
```
|
||
|
||
**Configuration:**
|
||
|
||
```yaml---
|
||
|
||
# Use defaults - no configuration needed!
|
||
|
||
best_price_flex: 15 # (default)## Common Scenarios
|
||
|
||
best_price_min_period_length: 60 # (default)
|
||
|
||
best_price_min_distance_from_avg: 2 # (default)### Scenario 1: Simple Best Price (Default)
|
||
|
||
```
|
||
|
||
**Goal:** Find the cheapest time each day to run dishwasher
|
||
|
||
**What you get:**
|
||
|
||
- 1-3 periods per day with prices ≤ MIN + 15%**Configuration:**
|
||
|
||
- Each period at least 1 hour long```yaml
|
||
|
||
- All periods at least 2% cheaper than daily average# Use defaults - no configuration needed!
|
||
|
||
best_price_flex: 15 # (default)
|
||
|
||
**Automation example:**best_price_min_period_length: 60 # (default)
|
||
|
||
```yamlbest_price_min_distance_from_avg: 2 # (default)
|
||
|
||
automation:```
|
||
|
||
- trigger:
|
||
|
||
- platform: state**What you get:**
|
||
|
||
entity_id: binary_sensor.tibber_home_best_price_period- 1-3 periods per day with prices ≤ MIN + 15%
|
||
|
||
to: "on"- Each period at least 1 hour long
|
||
|
||
action:- All periods at least 2% cheaper than daily average
|
||
|
||
- service: switch.turn_on
|
||
|
||
target:**Automation example:**
|
||
|
||
entity_id: switch.dishwasher```yaml
|
||
|
||
```automation:
|
||
|
||
- trigger:
|
||
|
||
### Scenario 2: Heat Pump (Long Periods + Relaxation) - platform: state
|
||
|
||
entity_id: binary_sensor.tibber_home_best_price_period
|
||
|
||
**Goal:** Run water heater during long cheap windows, accept longer periods even if not perfectly cheap to: "on"
|
||
|
||
action:
|
||
|
||
**Configuration:** - service: switch.turn_on
|
||
|
||
```yaml target:
|
||
|
||
best_price_min_period_length: 120 # Need at least 2 hours entity_id: switch.dishwasher
|
||
|
||
enable_min_periods_best: true```
|
||
|
||
min_periods_best: 2 # Want 2 opportunities per day
|
||
|
||
relaxation_step_best: 35### Scenario 2: Heat Pump (Long Periods + Relaxation)
|
||
|
||
best_price_max_level: cheap # Prefer CHEAP intervals
|
||
|
||
best_price_max_level_gap_count: 3 # But allow some NORMAL intervals**Goal:** Run water heater during long cheap windows, accept longer periods even if not perfectly cheap
|
||
|
||
```
|
||
|
||
**Configuration:**
|
||
|
||
**What you get:**```yaml
|
||
|
||
- At least 2 periods per day (relaxation ensures this)best_price_min_period_length: 120 # Need at least 2 hours
|
||
|
||
- Each period at least 2 hours longenable_min_periods_best: true
|
||
|
||
- Primarily CHEAP intervals, but tolerates up to 3 NORMAL intervals per periodmin_periods_best: 2 # Want 2 opportunities per day
|
||
|
||
- If not enough strict matches, relaxation finds longer/less-strict periodsrelaxation_step_best: 35
|
||
|
||
best_price_max_level: cheap # Prefer CHEAP intervals
|
||
|
||
**Automation example:**best_price_max_level_gap_count: 3 # But allow some NORMAL intervals
|
||
|
||
```yaml```
|
||
|
||
automation:
|
||
|
||
- trigger:**What you get:**
|
||
|
||
- platform: state- At least 2 periods per day (relaxation ensures this)
|
||
|
||
entity_id: binary_sensor.tibber_home_best_price_period- Each period at least 2 hours long
|
||
|
||
to: "on"- Primarily CHEAP intervals, but tolerates up to 3 NORMAL intervals per period
|
||
|
||
condition:- If not enough strict matches, relaxation finds longer/less-strict periods
|
||
|
||
- condition: numeric_state
|
||
|
||
entity_id: sensor.water_heater_temperature**Automation example:**
|
||
|
||
below: 50```yaml
|
||
|
||
action:automation:
|
||
|
||
- service: climate.set_hvac_mode - trigger:
|
||
|
||
target: - platform: state
|
||
|
||
entity_id: climate.water_heater entity_id: binary_sensor.tibber_home_best_price_period
|
||
|
||
data: to: "on"
|
||
|
||
hvac_mode: heat condition:
|
||
|
||
``` - condition: numeric_state
|
||
|
||
entity_id: sensor.water_heater_temperature
|
||
|
||
### Scenario 3: EV Charging (Stable Prices Only) below: 50
|
||
|
||
action:
|
||
|
||
**Goal:** Charge electric vehicle only during stable, predictable cheap prices - service: climate.set_hvac_mode
|
||
|
||
target:
|
||
|
||
**Configuration:** entity_id: climate.water_heater
|
||
|
||
```yaml data:
|
||
|
||
best_price_flex: 10 # Very strict (only very cheap times) hvac_mode: heat
|
||
|
||
best_price_min_volatility: moderate # Require stable prices```
|
||
|
||
best_price_max_level: cheap # Require at least one CHEAP interval
|
||
|
||
enable_min_periods_best: false # Don't relax - better to skip a day### Scenario 3: EV Charging (Stable Prices Only)
|
||
|
||
```
|
||
|
||
**Goal:** Charge electric vehicle only during stable, predictable cheap prices
|
||
|
||
**What you get:**
|
||
|
||
- Very strict matching - only clearly cheap, stable periods**Configuration:**
|
||
|
||
- Some days might have 0 periods (and that's OK)```yaml
|
||
|
||
- When periods appear, they're high confidencebest_price_flex: 10 # Very strict (only very cheap times)
|
||
|
||
best_price_min_volatility: moderate # Require stable prices
|
||
|
||
**Automation example:**best_price_max_level: cheap # Require at least one CHEAP interval
|
||
|
||
```yamlenable_min_periods_best: false # Don't relax - better to skip a day
|
||
|
||
automation:```
|
||
|
||
- trigger:
|
||
|
||
- platform: state**What you get:**
|
||
|
||
entity_id: binary_sensor.tibber_home_best_price_period- Very strict matching - only clearly cheap, stable periods
|
||
|
||
to: "on"- Some days might have 0 periods (and that's OK)
|
||
|
||
condition:- When periods appear, they're high confidence
|
||
|
||
- condition: numeric_state
|
||
|
||
entity_id: sensor.ev_battery_level**Automation example:**
|
||
|
||
below: 80```yaml
|
||
|
||
- condition: stateautomation:
|
||
|
||
entity_id: binary_sensor.ev_connected - trigger:
|
||
|
||
state: "on" - platform: state
|
||
|
||
action: entity_id: binary_sensor.tibber_home_best_price_period
|
||
|
||
- service: switch.turn_on to: "on"
|
||
|
||
target: condition:
|
||
|
||
entity_id: switch.ev_charger - condition: numeric_state
|
||
|
||
``` entity_id: sensor.ev_battery_level
|
||
|
||
below: 80
|
||
|
||
### Scenario 4: Peak Price Avoidance - condition: state
|
||
|
||
entity_id: binary_sensor.ev_connected
|
||
|
||
**Goal:** Reduce heating during the most expensive hours state: "on"
|
||
|
||
action:
|
||
|
||
**Configuration:** - service: switch.turn_on
|
||
|
||
```yaml target:
|
||
|
||
peak_price_flex: -10 # Only the very expensive times entity_id: switch.ev_charger
|
||
|
||
peak_price_min_period_length: 30 # Even short periods matter```
|
||
|
||
enable_min_periods_peak: true
|
||
|
||
min_periods_peak: 1 # Ensure at least 1 peak warning per day### Scenario 4: Peak Price Avoidance
|
||
|
||
```
|
||
|
||
**Goal:** Reduce heating during the most expensive hours
|
||
|
||
**What you get:**
|
||
|
||
- At least 1 expensive period per day (relaxation ensures this)**Configuration:**
|
||
|
||
- Periods can be as short as 30 minutes```yaml
|
||
|
||
- Clear signal when to reduce consumptionpeak_price_flex: -10 # Only the very expensive times
|
||
|
||
peak_price_min_period_length: 30 # Even short periods matter
|
||
|
||
**Automation example:**enable_min_periods_peak: true
|
||
|
||
```yamlmin_periods_peak: 1 # Ensure at least 1 peak warning per day
|
||
|
||
automation:```
|
||
|
||
- trigger:
|
||
|
||
- platform: state**What you get:**
|
||
|
||
entity_id: binary_sensor.tibber_home_peak_price_period- At least 1 expensive period per day (relaxation ensures this)
|
||
|
||
to: "on"- Periods can be as short as 30 minutes
|
||
|
||
action:- Clear signal when to reduce consumption
|
||
|
||
- service: climate.set_temperature
|
||
|
||
target:**Automation example:**
|
||
|
||
entity_id: climate.living_room```yaml
|
||
|
||
data:automation:
|
||
|
||
temperature: 19 # Reduce by 2°C during peaks - trigger:
|
||
|
||
``` - platform: state
|
||
|
||
entity_id: binary_sensor.tibber_home_peak_price_period
|
||
|
||
--- to: "on"
|
||
|
||
action:
|
||
|
||
## Troubleshooting - service: climate.set_temperature
|
||
|
||
target:
|
||
|
||
### No Periods Found entity_id: climate.living_room
|
||
|
||
data:
|
||
|
||
**Symptom:** `binary_sensor.tibber_home_best_price_period` never turns "on" temperature: 19 # Reduce by 2°C during peaks
|
||
|
||
```
|
||
|
||
**Possible causes:**
|
||
|
||
---
|
||
|
||
1. **Filters too strict**
|
||
|
||
```yaml## Troubleshooting
|
||
|
||
# Try:
|
||
|
||
best_price_flex: 20 # Increase from default 15%### No Periods Found
|
||
|
||
best_price_min_distance_from_avg: 1 # Reduce from default 2%
|
||
|
||
```**Symptom:** `binary_sensor.tibber_home_best_price_period` never turns "on"
|
||
|
||
|
||
|
||
2. **Period length too long****Possible causes:**
|
||
|
||
```yaml
|
||
|
||
# Try:1. **Filters too strict**
|
||
|
||
best_price_min_period_length: 45 # Reduce from default 60 minutes ```yaml
|
||
|
||
``` # Try:
|
||
|
||
best_price_flex: 20 # Increase from default 15%
|
||
|
||
3. **Flat price curve** (all prices very similar) best_price_min_distance_from_avg: 1 # Reduce from default 2%
|
||
|
||
- Enable relaxation to ensure at least some periods ```
|
||
|
||
```yaml
|
||
|
||
enable_min_periods_best: true2. **Period length too long**
|
||
|
||
min_periods_best: 1 ```yaml
|
||
|
||
``` # Try:
|
||
|
||
best_price_min_period_length: 45 # Reduce from default 60 minutes
|
||
|
||
### Too Many Periods ```
|
||
|
||
|
||
|
||
**Symptom:** 5+ periods per day, hard to decide which one to use3. **Flat price curve** (all prices very similar)
|
||
|
||
- Enable relaxation to ensure at least some periods
|
||
|
||
**Solution:** ```yaml
|
||
|
||
```yaml enable_min_periods_best: true
|
||
|
||
# Make filters stricter: min_periods_best: 1
|
||
|
||
best_price_flex: 10 # Reduce from default 15% ```
|
||
|
||
best_price_min_period_length: 90 # Increase from default 60 minutes
|
||
|
||
best_price_min_volatility: moderate # Require stable prices
|
||
|
||
best_price_max_level: cheap # Require CHEAP intervals**Symptom:** 5+ periods per day, hard to decide which one to use
|
||
|
||
```
|
||
|
||
**Solution:**
|
||
|
||
### Periods Split Into Small Pieces```yaml
|
||
|
||
# Make filters stricter:
|
||
|
||
**Symptom:** Many short periods instead of one long periodbest_price_flex: 10 # Reduce from default 15%
|
||
|
||
best_price_min_period_length: 90 # Increase from default 60 minutes
|
||
|
||
**Possible causes:**best_price_min_volatility: moderate # Require stable prices
|
||
|
||
best_price_max_level: cheap # Require CHEAP intervals
|
||
|
||
1. **Level filter too strict**```
|
||
|
||
```yaml
|
||
|
||
# One "NORMAL" interval splits an otherwise good period### Periods Split Into Small Pieces
|
||
|
||
# Solution: Use gap tolerance
|
||
|
||
best_price_max_level: cheap**Symptom:** Many short periods instead of one long period
|
||
|
||
best_price_max_level_gap_count: 2 # Allow 2 NORMAL intervals
|
||
|
||
```**Possible causes:**
|
||
|
||
|
||
|
||
2. **Flexibility too tight**1. **Level filter too strict**
|
||
|
||
```yaml ```yaml
|
||
|
||
# One interval just outside flex range splits the period # One "NORMAL" interval splits an otherwise good period
|
||
|
||
# Solution: Increase flexibility # Solution: Use gap tolerance
|
||
|
||
best_price_flex: 20 # Increase from 15% best_price_max_level: cheap
|
||
|
||
``` best_price_max_level_gap_count: 2 # Allow 2 NORMAL intervals
|
||
|
||
```
|
||
|
||
### Understanding Sensor Attributes
|
||
|
||
2. **Flexibility too tight**
|
||
|
||
**Check period details:** ```yaml
|
||
|
||
```yaml # One interval just outside flex range splits the period
|
||
|
||
# Entity: binary_sensor.tibber_home_best_price_period # Solution: Increase flexibility
|
||
|
||
best_price_flex: 20 # Increase from 15%
|
||
|
||
# Attributes when "on": ```
|
||
|
||
start: "2025-11-11T02:00:00+01:00"
|
||
|
||
end: "2025-11-11T05:00:00+01:00"### Understanding Sensor Attributes
|
||
|
||
duration_minutes: 180
|
||
|
||
rating_level: "LOW" # All intervals are LOW price**Check period details:**
|
||
|
||
price_avg: 18.5 # Average price in this period```yaml
|
||
|
||
relaxation_active: true # This day used relaxation# Entity: binary_sensor.tibber_home_best_price_period
|
||
|
||
relaxation_level: "price_diff_20.25%+level_any" # Found at flex 20.25%, level filter removed
|
||
|
||
# Attributes when "on":
|
||
|
||
# When "off" (outside any period):start: "2025-11-11T02:00:00+01:00"
|
||
|
||
next_start: "2025-11-11T14:00:00+01:00" # Next period starts at 14:00end: "2025-11-11T05:00:00+01:00"
|
||
|
||
next_end: "2025-11-11T17:00:00+01:00"duration_minutes: 180
|
||
|
||
next_duration_minutes: 180rating_level: "LOW" # All intervals are LOW price
|
||
|
||
```price_avg: 18.5 # Average price in this period
|
||
|
||
relaxation_active: true # This day used relaxation
|
||
|
||
### Checking the Logsrelaxation_level: "price_diff_20.25%+level_any" # Found at flex 20.25%, level filter removed
|
||
|
||
|
||
|
||
Enable debug logging to see detailed calculation:# When "off" (outside any period):
|
||
|
||
next_start: "2025-11-11T14:00:00+01:00" # Next period starts at 14:00
|
||
|
||
```yamlnext_end: "2025-11-11T17:00:00+01:00"
|
||
|
||
# configuration.yamlnext_duration_minutes: 180
|
||
|
||
logger:```
|
||
|
||
default: warning
|
||
|
||
logs:### Checking the Logs
|
||
|
||
custom_components.tibber_prices.period_utils: debug
|
||
|
||
```Enable debug logging to see detailed calculation:
|
||
|
||
|
||
|
||
**What to look for:**```yaml
|
||
|
||
```# configuration.yaml
|
||
|
||
INFO: Calculating BEST PRICE periods: relaxation=ON, target=2/day, flex=15.0%logger:
|
||
|
||
DEBUG: Day 2025-11-11: Found 1 baseline period (need 2) default: warning
|
||
|
||
DEBUG: Day 2025-11-11: Starting relaxation... logs:
|
||
|
||
DEBUG: Phase 1: flex 20.25% + original filters custom_components.tibber_prices.period_utils: debug
|
||
|
||
DEBUG: Candidate: 02:00-05:00 (3h) - rating=LOW, avg=18.5 ct```
|
||
|
||
DEBUG: Result: 2 standalone periods after merge ✓
|
||
|
||
INFO: Day 2025-11-11: Success after 1 relaxation phase (2 periods)**What to look for:**
|
||
|
||
``````
|
||
|
||
INFO: Calculating BEST PRICE periods: relaxation=ON, target=2/day, flex=15.0%
|
||
|
||
---DEBUG: Day 2025-11-11: Found 1 baseline period (need 2)
|
||
|
||
DEBUG: Day 2025-11-11: Starting relaxation...
|
||
|
||
## Advanced TopicsDEBUG: Phase 1: flex 20.25% + original filters
|
||
|
||
DEBUG: Candidate: 02:00-05:00 (3h) - rating=LOW, avg=18.5 ct
|
||
|
||
For advanced configuration patterns and technical deep-dive, see:DEBUG: Result: 2 standalone periods after merge ✓
|
||
|
||
- [Automation Examples](./automation-examples.md) - Real-world automation patternsINFO: Day 2025-11-11: Success after 1 relaxation phase (2 periods)
|
||
|
||
- [Services](./services.md) - Using the `tibber_prices.get_price` service for custom logic```
|
||
|
||
|
||
|
||
### Quick Reference---
|
||
|
||
|
||
|
||
**Configuration Parameters:**## Advanced Topics
|
||
|
||
|
||
|
||
| Parameter | Default | Range | Purpose |For advanced configuration patterns and technical deep-dive, see:
|
||
|
||
|-----------|---------|-------|---------|- [Automation Examples](./automation-examples.md) - Real-world automation patterns
|
||
|
||
| `best_price_flex` | 15% | 0-100% | Search range from daily MIN |- [Services](./services.md) - Using the `tibber_prices.get_price` service for custom logic
|
||
|
||
| `best_price_min_period_length` | 60 min | 15-240 | Minimum duration |
|
||
|
||
| `best_price_min_distance_from_avg` | 2% | 0-20% | Quality threshold |### Quick Reference
|
||
|
||
| `best_price_min_volatility` | low | low/mod/high/vhigh | Stability filter |
|
||
|
||
| `best_price_max_level` | any | any/cheap/vcheap | Absolute quality |**Configuration Parameters:**
|
||
|
||
| `best_price_max_level_gap_count` | 0 | 0-10 | Gap tolerance |
|
||
|
||
| `enable_min_periods_best` | false | true/false | Enable relaxation || Parameter | Default | Range | Purpose |
|
||
|
||
| `min_periods_best` | - | 1-10 | Target periods per day ||-----------|---------|-------|---------|
|
||
|
||
| `relaxation_step_best` | - | 5-100% | Relaxation increment || `best_price_flex` | 15% | 0-100% | Search range from daily MIN |
|
||
|
||
| `best_price_min_period_length` | 60 min | 15-240 | Minimum duration |
|
||
|
||
**Peak Price:** Same parameters with `peak_price_*` prefix (defaults: flex=-15%, same otherwise)| `best_price_min_distance_from_avg` | 2% | 0-20% | Quality threshold |
|
||
|
||
| `best_price_min_volatility` | low | low/mod/high/vhigh | Stability filter |
|
||
|
||
### Price Levels Reference| `best_price_max_level` | any | any/cheap/vcheap | Absolute quality |
|
||
|
||
| `best_price_max_level_gap_count` | 0 | 0-10 | Gap tolerance |
|
||
|
||
The Tibber API provides price levels for each 15-minute interval:| `enable_min_periods_best` | false | true/false | Enable relaxation |
|
||
|
||
| `min_periods_best` | - | 1-10 | Target periods per day |
|
||
|
||
**Levels (based on trailing 24h average):**| `relaxation_step_best` | - | 5-100% | Relaxation increment |
|
||
|
||
- `VERY_CHEAP` - Significantly below average
|
||
|
||
- `CHEAP` - Below average**Peak Price:** Same parameters with `peak_price_*` prefix (defaults: flex=-15%, same otherwise)
|
||
|
||
- `NORMAL` - Around average
|
||
|
||
- `EXPENSIVE` - Above average### Price Levels Reference
|
||
|
||
- `VERY_EXPENSIVE` - Significantly above average
|
||
|
||
The Tibber API provides price levels for each 15-minute interval:
|
||
|
||
**Note:** Your configured `best_price_max_level` or `peak_price_min_level` filter uses these API-provided levels.
|
||
|
||
**Levels (based on trailing 24h average):**
|
||
|
||
---- `VERY_CHEAP` - Significantly below average
|
||
|
||
- `CHEAP` - Below average
|
||
|
||
**Last updated:** November 11, 2025 - `NORMAL` - Around average
|
||
|
||
**Integration version:** 2.0+- `EXPENSIVE` - Above average
|
||
|
||
- `VERY_EXPENSIVE` - Significantly above average
|
||
|
||
**Note:** Your configured `best_price_max_level` or `peak_price_min_level` filter uses these API-provided levels.
|
||
|
||
---
|
||
|
||
**Last updated:** November 11, 2025
|
||
**Integration version:** 2.0+
|
||
|
||
### Best Price Period Settings
|
||
|
||
| Option | Default | Description | Acts in Step |
|
||
|--------|---------|-------------|--------------|
|
||
| `best_price_flex` | 15% | How much more expensive than the daily **MIN** can an interval be? | 2 (Identification) |
|
||
| `best_price_min_period_length` | 60 min | Minimum length of a period | 3 (Length filter) |
|
||
| `best_price_min_distance_from_avg` | 2% | Minimum distance below daily **average** (separate from flexibility) | 4 (Quality filter) |
|
||
| `best_price_min_volatility` | LOW | Minimum volatility within the period (optional) | 5 (Volatility filter) |
|
||
| `best_price_max_level` | ANY | Maximum price level (optional, e.g., only CHEAP or better) | 5 (Level filter) |
|
||
| `best_price_max_level_gap_count` | 0 | Tolerance for level deviations (see [Gap Tolerance](#gap-tolerance-for-level-filters)) | 5 (Level filter) |
|
||
| `enable_min_periods_best` | Off | Enables relaxation mechanism | - (Relaxation) |
|
||
| `min_periods_best` | 2 | Minimum number of periods **per day** to achieve | - (Relaxation) |
|
||
| `relaxation_step_best` | 25% | Step size for filter relaxation | - (Relaxation) |
|
||
|
||
### Peak Price Period Settings
|
||
|
||
| Option | Default | Description | Acts in Step |
|
||
|--------|---------|-------------|--------------|
|
||
| `peak_price_flex` | -15% | How much less expensive than the daily **MAX** can an interval be? | 2 (Identification) |
|
||
| `peak_price_min_period_length` | 60 min | Minimum length of a period | 3 (Length filter) |
|
||
| `peak_price_min_distance_from_avg` | 2% | Minimum distance above daily **average** (separate from flexibility) | 4 (Quality filter) |
|
||
| `peak_price_min_volatility` | LOW | Minimum volatility within the period (optional) | 5 (Volatility filter) |
|
||
| `peak_price_min_level` | ANY | Minimum price level (optional, e.g., only EXPENSIVE or higher) | 5 (Level filter) |
|
||
| `peak_price_max_level_gap_count` | 0 | Tolerance for level deviations (see [Gap Tolerance](#gap-tolerance-for-level-filters)) | 5 (Level filter) |
|
||
| `enable_min_periods_peak` | Off | Enables relaxation mechanism | - (Relaxation) |
|
||
| `min_periods_peak` | 2 | Minimum number of periods **per day** to achieve | - (Relaxation) |
|
||
| `relaxation_step_peak` | 25% | Step size for filter relaxation | - (Relaxation) |
|
||
|
||
---
|
||
|
||
## Filter Pipeline
|
||
|
||
After basic period identification (Steps 1-4), two optional **additional filters** can be applied:
|
||
|
||
### Volatility Filter
|
||
|
||
**Purpose:** Only show periods when the price spread within the period is large enough.
|
||
|
||
**Use case:**
|
||
- **Best Price**: "I only want to optimize when it's really worth it" (high volatility)
|
||
- **Peak Price**: "Only warn me about large price swings" (high volatility)
|
||
|
||
**How it works:**
|
||
```
|
||
Period: 00:00-01:00
|
||
Intervals: 20.5 | 19.8 | 21.0 | 20.2 ct/kWh
|
||
Min: 19.8 ct, Max: 21.0 ct
|
||
Volatility (spread): 21.0 - 19.8 = 1.2 ct/kWh
|
||
|
||
Volatility thresholds:
|
||
- LOW: < 5.0 ct → This period: LOW
|
||
- MODERATE: 5-15 ct
|
||
- HIGH: 15-30 ct
|
||
- VERY_HIGH: ≥ 30 ct
|
||
|
||
best_price_min_volatility = "MODERATE" (5 ct)
|
||
→ Period is REJECTED (1.2 ct < 5.0 ct)
|
||
```
|
||
|
||
**Configuration:**
|
||
- `best_price_min_volatility`: `low` | `moderate` | `high` | `very_high`
|
||
- `peak_price_min_volatility`: `low` | `moderate` | `high` | `very_high`
|
||
|
||
**Default:** `low` (filter disabled, all periods shown)
|
||
|
||
### Level Filter (Price Level)
|
||
|
||
**Purpose:** Only show periods that are actually cheap/expensive in absolute terms, not just relative to the daily average.
|
||
|
||
**Use case:**
|
||
- **Best Price**: "Only show best price when there's at least one CHEAP interval" (not just "less expensive than usual today")
|
||
- **Peak Price**: "Only show peak price when there's at least one EXPENSIVE interval" (not just "more expensive than average")
|
||
|
||
**Price levels (from Tibber API):**
|
||
- `VERY_CHEAP` (-2)
|
||
- `CHEAP` (-1)
|
||
- `NORMAL` (0)
|
||
- `EXPENSIVE` (+1)
|
||
- `VERY_EXPENSIVE` (+2)
|
||
|
||
**How it works (Best Price example):**
|
||
```
|
||
best_price_max_level = "CHEAP"
|
||
|
||
Period: 00:00-01:00
|
||
Intervals with levels:
|
||
00:00: 20.5 ct → CHEAP ✓
|
||
00:15: 19.8 ct → VERY_CHEAP ✓
|
||
00:30: 21.0 ct → NORMAL ✗
|
||
00:45: 20.2 ct → CHEAP ✓
|
||
|
||
Filter logic (without gap tolerance):
|
||
→ Does the period have at least ONE interval with level ≤ CHEAP?
|
||
→ YES (three intervals are CHEAP or better)
|
||
→ Period is KEPT
|
||
|
||
But: One NORMAL interval in the middle!
|
||
→ Without gap tolerance: Period is split into two parts
|
||
→ With gap tolerance: Period stays together (see next section)
|
||
```
|
||
|
||
**Configuration:**
|
||
- `best_price_max_level`: `any` | `very_cheap` | `cheap` | `normal` | `expensive`
|
||
- `peak_price_min_level`: `any` | `expensive` | `normal` | `cheap` | `very_cheap`
|
||
|
||
**Default:** `any` (filter disabled)
|
||
|
||
---
|
||
|
||
## Gap Tolerance for Level Filters
|
||
|
||
### Problem Without Gap Tolerance
|
||
|
||
When you activate a level filter (e.g., `best_price_max_level = "CHEAP"`), periods are **strictly filtered**:
|
||
|
||
```
|
||
Period: 00:00-02:00 (2 hours)
|
||
Intervals:
|
||
00:00-01:30: CHEAP, CHEAP, CHEAP, CHEAP, CHEAP, CHEAP
|
||
01:30-01:45: NORMAL ← A single deviating interval!
|
||
01:45-02:00: CHEAP
|
||
|
||
Without gap tolerance:
|
||
→ Period is split into TWO periods:
|
||
1. 00:00-01:30 (1.5h)
|
||
2. 01:45-02:00 (0.25h) ✗ too short, discarded!
|
||
→ Result: Only 1.5h best price instead of 2h
|
||
```
|
||
|
||
### Solution: Gap Tolerance
|
||
|
||
**Gap tolerance** allows a configurable number of intervals that deviate by **exactly one level step** from the required level.
|
||
|
||
**How it works:**
|
||
|
||
1. **"Gap" definition:** An interval that deviates by exactly 1 level step
|
||
```
|
||
Best Price filter: CHEAP (-1)
|
||
NORMAL (0) is +1 step → GAP ✓
|
||
EXPENSIVE (+1) is +2 steps → NOT A GAP, too far away
|
||
```
|
||
|
||
2. **Gap counting:** Max X gaps allowed per period (configurable: 0-8)
|
||
|
||
3. **Minimum distance between gaps:** Gaps must not be too close together
|
||
```
|
||
Dynamic formula: max(2, (interval_count / max_gaps) / 2)
|
||
|
||
Example: 16 intervals, max 2 gaps allowed
|
||
→ Minimum distance: max(2, (16/2)/2) = max(2, 4) = 4 intervals
|
||
|
||
CHEAP, CHEAP, CHEAP, CHEAP, NORMAL, CHEAP, CHEAP, CHEAP, NORMAL, CHEAP
|
||
↑ GAP1 ↑ GAP2
|
||
└─────── 4 intervals ──────────────┘
|
||
→ OK, minimum distance maintained
|
||
```
|
||
|
||
4. **25% cap:** Maximum 25% of a period's intervals can be gaps
|
||
```
|
||
Period: 12 intervals, user configured 5 gaps
|
||
→ Effective: min(5, 12/4) = min(5, 3) = 3 gaps allowed
|
||
```
|
||
|
||
5. **Minimum period length:** Gap tolerance only applies to periods ≥ 1.5h (6 intervals)
|
||
```
|
||
Period < 1.5h: Strict filtering (0 tolerance)
|
||
Period ≥ 1.5h: Gap tolerance as configured
|
||
```
|
||
|
||
### Gap Cluster Splitting
|
||
|
||
If a period would still be rejected **despite gap tolerance** (too many gaps or too dense), the integration tries to **intelligently split** it:
|
||
|
||
```
|
||
Period: 00:00-04:00 (16 intervals)
|
||
CHEAP, CHEAP, CHEAP, NORMAL, NORMAL, NORMAL, CHEAP, CHEAP, ..., CHEAP
|
||
└─ Gap cluster (3×) ─┘
|
||
|
||
Gap cluster = 2+ consecutive deviating intervals
|
||
|
||
→ Splitting at gap cluster:
|
||
1. 00:00-00:45 (3 intervals) ✗ too short
|
||
2. 01:30-04:00 (10 intervals) ✓ kept
|
||
|
||
→ Result: 2.5h best price instead of complete rejection
|
||
```
|
||
|
||
### Configuration
|
||
|
||
**Best Price:**
|
||
```yaml
|
||
best_price_max_level: "cheap" # Enable level filter
|
||
best_price_max_level_gap_count: 2 # Allow 2 NORMAL intervals per period
|
||
```
|
||
|
||
**Peak Price:**
|
||
```yaml
|
||
peak_price_min_level: "expensive" # Enable level filter
|
||
peak_price_max_level_gap_count: 1 # Allow 1 NORMAL interval per period
|
||
```
|
||
|
||
**Default:** `0` (no tolerance, strict filtering)
|
||
|
||
### Example Scenarios
|
||
|
||
#### Scenario 1: Conservative (0 gaps)
|
||
```yaml
|
||
best_price_max_level: "cheap"
|
||
best_price_max_level_gap_count: 0 # Default
|
||
```
|
||
|
||
**Behavior:**
|
||
- Every interval MUST be CHEAP or better
|
||
- A single NORMAL interval → period is split
|
||
|
||
**Good for:** Users who want absolute price guarantees
|
||
|
||
#### Scenario 2: Moderate (2-3 gaps)
|
||
```yaml
|
||
best_price_max_level: "cheap"
|
||
best_price_max_level_gap_count: 2
|
||
```
|
||
|
||
**Behavior:**
|
||
- Up to 2 NORMAL intervals per period tolerated
|
||
- Minimum distance between gaps dynamically calculated
|
||
- 25% cap protects against too many gaps
|
||
|
||
**Good for:** Most users - balance between quality and period length
|
||
|
||
#### Scenario 3: Aggressive (5-8 gaps)
|
||
```yaml
|
||
best_price_max_level: "cheap"
|
||
best_price_max_level_gap_count: 5
|
||
```
|
||
|
||
**Behavior:**
|
||
- Up to 5 NORMAL intervals (but max 25% of period)
|
||
- Longer periods possible
|
||
- Quality may suffer (more "not-quite-so-cheap" intervals)
|
||
|
||
**Good for:** Users with flexible devices that need long run times
|
||
|
||
---
|
||
|
||
## Relaxation Mechanism
|
||
|
||
If **too few periods** are found despite all filters, the integration can automatically **gradually relax** filters.
|
||
|
||
### When is Relaxation Applied?
|
||
|
||
Only when **both conditions** are met:
|
||
1. `enable_min_periods_best/peak` is enabled
|
||
2. Fewer than `min_periods_best/peak` periods found **for a specific day**
|
||
|
||
**Important:** The minimum period requirement is checked **separately for each day** (today and tomorrow). This ensures:
|
||
- Each day must have enough periods independently
|
||
- Today can meet the requirement while tomorrow doesn't (or vice versa)
|
||
- When tomorrow's prices arrive, both days are evaluated separately
|
||
|
||
**Example scenario:**
|
||
- Configuration: `min_periods_best = 3`
|
||
- 14:00: Tomorrow's prices arrive
|
||
- Today: 10 periods remaining → ✅ Meets requirement (≥3)
|
||
- Tomorrow: 2 periods found → ❌ Doesn't meet requirement (<3)
|
||
- **Result:** Relaxation only applies to tomorrow's periods
|
||
|
||
### Relaxation Levels
|
||
|
||
The integration tries to relax filters in this order:
|
||
|
||
#### Level 1: Relax Flexibility
|
||
```
|
||
Original: best_price_flex = 15%
|
||
Step 1: 15% + (15% × 0.25) = 18.75%
|
||
Step 2: 18.75% + (18.75% × 0.25) = 23.44%
|
||
Step 3: ...
|
||
```
|
||
|
||
**Calculation:** `new_flexibility = old_flexibility × (1 + relaxation_step / 100)`
|
||
|
||
**Important:** This increases the flexibility percentage, which allows intervals **further from the daily MIN/MAX** to be included. For best price, this means accepting intervals more expensive than the original flexibility threshold.
|
||
|
||
#### Level 2: Disable Volatility Filter
|
||
```
|
||
If flexibility relaxation isn't enough:
|
||
→ best_price_min_volatility = "any" (filter off)
|
||
```
|
||
|
||
#### Level 3: Disable All Filters
|
||
```
|
||
If still too few periods:
|
||
→ Volatility = "any"
|
||
→ Level filter = "any"
|
||
→ Only flexibility and minimum length active
|
||
```
|
||
|
||
### Relaxation Status
|
||
|
||
The sensors show the **relaxation status** as an attribute:
|
||
|
||
```yaml
|
||
Best Price Period: # sensor.tibber_home_best_price_period
|
||
state: "on"
|
||
attributes:
|
||
relaxation_level: "volatility_any" # Volatility filter was disabled
|
||
```
|
||
|
||
**Possible values:**
|
||
- `none` - No relaxation, normal filters
|
||
- `volatility_any` - Volatility filter disabled
|
||
- `all_filters_off` - All optional filters disabled
|
||
|
||
### Example Configuration
|
||
|
||
```yaml
|
||
# Best Price: Try to find at least 2 periods
|
||
enable_min_periods_best: true
|
||
min_periods_best: 2
|
||
relaxation_step_best: 25 # 25% per step
|
||
|
||
best_price_flex: 15
|
||
best_price_min_volatility: "moderate"
|
||
```
|
||
|
||
**Process on a day with little price spread:**
|
||
1. Try with 15% flex + MODERATE volatility → 0 periods
|
||
2. Relax to 18.75% flex → 1 period
|
||
3. Relax to 23.44% flex → 1 period (still < 2)
|
||
4. Disable volatility filter → 2 periods ✓
|
||
|
||
**Result:** User sees 2 periods with `relaxation_level: "volatility_any"`
|
||
|
||
---
|
||
|
||
## Practical Examples
|
||
|
||
### Example 1: Standard Configuration (Best Price)
|
||
|
||
**Configuration:**
|
||
```yaml
|
||
best_price_flex: 15
|
||
best_price_min_period_length: 60
|
||
best_price_min_distance_from_avg: 2
|
||
best_price_min_volatility: "low" # Filter disabled
|
||
best_price_max_level: "any" # Filter disabled
|
||
```
|
||
|
||
**Daily prices:**
|
||
```
|
||
MIN: 18.0 ct/kWh
|
||
MAX: 32.0 ct/kWh
|
||
AVG: 25.0 ct/kWh
|
||
|
||
00:00-02:00: 18-20 ct (cheap)
|
||
06:00-08:00: 28-30 ct (expensive)
|
||
12:00-14:00: 24-26 ct (normal)
|
||
18:00-20:00: 19-21 ct (cheap)
|
||
```
|
||
|
||
**Calculation:**
|
||
1. Flexibility threshold: 18.0 × 1.15 = 20.7 ct (vs MIN, not average!)
|
||
2. Minimum distance threshold: 25.0 × 0.98 = 24.5 ct (vs AVG)
|
||
3. Both conditions: Price ≤ 20.7 ct AND Price ≤ 24.5 ct
|
||
|
||
**Result:**
|
||
- ✓ 00:00-02:00 (18-20 ct, all ≤ 20.7 and all ≤ 24.5)
|
||
- ✗ 06:00-08:00 (too expensive)
|
||
- ✗ 12:00-14:00 (24-26 ct, exceeds flexibility threshold of 20.7 ct)
|
||
- ✓ 18:00-20:00 (19-21 ct, all ≤ 20.7 and all ≤ 24.5)
|
||
|
||
**2 Best Price periods found!**
|
||
|
||
### Example 2: Strict Level Filter Without Gap Tolerance
|
||
|
||
**Configuration:**
|
||
```yaml
|
||
best_price_flex: 15
|
||
best_price_max_level: "cheap"
|
||
best_price_max_level_gap_count: 0 # No tolerance
|
||
```
|
||
|
||
**Period candidate:**
|
||
```
|
||
00:00-02:00:
|
||
00:00-01:30: CHEAP, CHEAP, CHEAP, CHEAP, CHEAP, CHEAP
|
||
01:30-01:45: NORMAL ← Deviation!
|
||
01:45-02:00: CHEAP
|
||
```
|
||
|
||
**Result:**
|
||
- ✗ Period is split into 00:00-01:30 and 01:45-02:00
|
||
- ✗ 01:45-02:00 too short (15 min < 60 min) → discarded
|
||
- ✓ Only 00:00-01:30 (1.5h) remains
|
||
|
||
### Example 3: Level Filter With Gap Tolerance
|
||
|
||
**Configuration:**
|
||
```yaml
|
||
best_price_flex: 15
|
||
best_price_max_level: "cheap"
|
||
best_price_max_level_gap_count: 2 # 2 gaps allowed
|
||
```
|
||
|
||
**Period candidate (same as above):**
|
||
```
|
||
00:00-02:00:
|
||
00:00-01:30: CHEAP, CHEAP, CHEAP, CHEAP, CHEAP, CHEAP
|
||
01:30-01:45: NORMAL ← Gap (1 of 2 allowed)
|
||
01:45-02:00: CHEAP
|
||
```
|
||
|
||
**Gap tolerance check:**
|
||
- Gaps found: 1 (NORMAL)
|
||
- Max allowed: 2
|
||
- 25% cap: min(2, 8/4) = 2 (8 intervals)
|
||
- Minimum distance: N/A (only 1 gap)
|
||
|
||
**Result:**
|
||
- ✓ Period stays as a whole: 00:00-02:00 (2h)
|
||
- 1 NORMAL interval is tolerated
|
||
|
||
### Example 4: Gap Cluster Gets Split
|
||
|
||
**Configuration:**
|
||
```yaml
|
||
best_price_flex: 15
|
||
best_price_max_level: "cheap"
|
||
best_price_max_level_gap_count: 2
|
||
```
|
||
|
||
**Period candidate:**
|
||
```
|
||
00:00-04:00 (16 intervals):
|
||
00:00-01:00: CHEAP, CHEAP, CHEAP, CHEAP (4)
|
||
01:00-02:00: NORMAL, NORMAL, NORMAL, NORMAL (4) ← Gap cluster!
|
||
02:00-04:00: CHEAP, CHEAP, CHEAP, ..., CHEAP (8)
|
||
```
|
||
|
||
**Gap tolerance check:**
|
||
- Gaps found: 4 (too many)
|
||
- Max allowed: 2
|
||
- → Normal check fails
|
||
|
||
**Gap cluster splitting:**
|
||
- Detect cluster: 4× consecutive NORMAL intervals
|
||
- Split period at cluster boundaries:
|
||
1. 00:00-01:00 (4 intervals = 60 min) ✓
|
||
2. 02:00-04:00 (8 intervals = 120 min) ✓
|
||
|
||
**Result:**
|
||
- ✓ Two separate periods: 00:00-01:00 and 02:00-04:00
|
||
- Total 3h best price (instead of complete rejection)
|
||
|
||
### Example 5: Relaxation in Action
|
||
|
||
**Configuration:**
|
||
```yaml
|
||
enable_min_periods_best: true
|
||
min_periods_best: 2
|
||
relaxation_step_best: 25
|
||
|
||
best_price_flex: 5 # Very strict!
|
||
best_price_min_volatility: "high" # Very strict!
|
||
```
|
||
|
||
**Day with little price spread:**
|
||
```
|
||
MIN: 23.0 ct/kWh
|
||
MAX: 27.0 ct/kWh
|
||
AVG: 25.0 ct/kWh
|
||
All prices between 23-27 ct (low volatility)
|
||
```
|
||
|
||
**Relaxation process:**
|
||
|
||
1. **Attempt 1:** 5% flex + HIGH volatility
|
||
```
|
||
Threshold: 23.0 × 1.05 = 24.15 ct (vs MIN)
|
||
No period meets both conditions
|
||
→ 0 periods (< 2 required)
|
||
```
|
||
|
||
2. **Attempt 2:** 6.25% flex + HIGH volatility
|
||
```
|
||
Threshold: 23.0 × 1.0625 = 24.44 ct
|
||
Still 0 periods
|
||
```
|
||
|
||
3. **Attempt 3:** Disable volatility filter
|
||
```
|
||
6.25% flex + ANY volatility
|
||
→ 1 period found (< 2)
|
||
```
|
||
|
||
4. **Attempt 4:** 7.81% flex + ANY volatility
|
||
```
|
||
Threshold: 23.0 × 1.0781 = 24.80 ct
|
||
→ 2 periods found ✓
|
||
```
|
||
|
||
**Result:**
|
||
- Sensor shows 2 periods with `relaxation_level: "volatility_any"`
|
||
- User knows: "Filters were relaxed to reach minimum count"
|
||
|
||
---
|
||
|
||
## Troubleshooting
|
||
|
||
### Problem: No Periods Found
|
||
|
||
**Possible causes:**
|
||
|
||
1. **Too strict flexibility**
|
||
```
|
||
best_price_flex: 5 # Only allows intervals ≤5% above daily MIN
|
||
```
|
||
**Solution:** Increase to 10-15%
|
||
|
||
2. **Too strict level filter without gap tolerance**
|
||
```
|
||
best_price_max_level: "very_cheap"
|
||
best_price_max_level_gap_count: 0
|
||
```
|
||
**Solution:** Relax level to "cheap" or enable gap tolerance (1-2)
|
||
|
||
3. **Too high volatility requirement**
|
||
```
|
||
best_price_min_volatility: "very_high"
|
||
```
|
||
**Solution:** Reduce to "moderate" or "low"
|
||
|
||
4. **Too long minimum period length**
|
||
```
|
||
best_price_min_period_length: 180 # 3 hours
|
||
```
|
||
**Solution:** Reduce to 60-90 minutes
|
||
|
||
5. **Day with very small price spread**
|
||
```
|
||
MIN: 23 ct, MAX: 27 ct (hardly any differences)
|
||
```
|
||
**Solution:** Enable relaxation mechanism:
|
||
```yaml
|
||
enable_min_periods_best: true
|
||
min_periods_best: 1
|
||
```
|
||
|
||
### Problem: Too Many Periods
|
||
|
||
**Solution:** Make filters stricter:
|
||
|
||
```yaml
|
||
best_price_flex: 20 # Reduce to 10-15
|
||
best_price_min_volatility: "moderate" # Require higher volatility
|
||
best_price_max_level: "cheap" # Only truly cheap times
|
||
```
|
||
|
||
### Problem: Periods Are Too Short
|
||
|
||
**Solution:** Increase minimum length and use gap tolerance:
|
||
|
||
```yaml
|
||
best_price_min_period_length: 90 # 1.5 hours
|
||
best_price_max_level_gap_count: 2 # Tolerate deviations
|
||
```
|
||
|
||
### Problem: Periods With "Mediocre" Prices
|
||
|
||
**Solution:** Increase minimum distance:
|
||
|
||
```yaml
|
||
best_price_min_distance_from_avg: 5 # Must be 5% below average
|
||
```
|
||
|
||
### Problem: Relaxation Applied Too Aggressively
|
||
|
||
**Solution:** Reduce step size:
|
||
|
||
```yaml
|
||
relaxation_step_best: 10 # Smaller steps (instead of 25)
|
||
```
|
||
|
||
Or disable relaxation completely:
|
||
|
||
```yaml
|
||
enable_min_periods_best: false
|
||
```
|
||
|
||
### Problem: Gap Tolerance Not Working As Expected
|
||
|
||
**Possible causes:**
|
||
|
||
1. **Period too short (< 1.5h)**
|
||
```
|
||
Gap tolerance only applies to periods ≥ 1.5h
|
||
```
|
||
**Solution:** Reduce `best_price_min_period_length` or adjust flexibility
|
||
|
||
2. **25% cap limiting effective gaps**
|
||
```
|
||
Period: 8 intervals, configured 4 gaps
|
||
→ Effective: min(4, 8/4) = 2 gaps
|
||
```
|
||
**Solution:** Accept limitation or relax level filter
|
||
|
||
3. **Gaps too close together**
|
||
```
|
||
Minimum distance between gaps not maintained
|
||
```
|
||
**Solution:** Increase gap count or accept splitting
|
||
|
||
---
|
||
|
||
## Further Documentation
|
||
|
||
- **[Configuration Guide](configuration.md)** - UI screenshots and step-by-step guide
|
||
- **[Sensors](sensors.md)** - All available sensors and attributes
|
||
- **[Automation Examples](automation-examples.md)** - Practical automation recipes with periods
|
||
- **[Developer Documentation](../development/)** - Code architecture and algorithm details
|
||
|
||
---
|
||
|
||
**Questions or feedback?** Open an [issue on GitHub](https://github.com/jpawlowski/hass.tibber_prices/issues)!
|