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https://github.com/jpawlowski/hass.tibber_prices.git
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refactor(period_utils): simplify period qualification logic by removing average boundary check
This commit is contained in:
Julian Pawlowski
parent
e0b8cdc072
commit
7605e88b96
2 changed files with 96 additions and 56 deletions
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@ -269,7 +269,6 @@ def _build_periods(
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# Check if interval qualifies for the period
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in_flex = percent_diff >= flex * 100 if reverse_sort else percent_diff <= flex * 100
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within_avg_boundary = price >= avg_price if reverse_sort else price <= avg_price
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# Minimum distance from average
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if reverse_sort:
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@ -289,7 +288,7 @@ def _build_periods(
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last_ref_date = date_key
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# Add to period if all criteria are met
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if in_flex and within_avg_boundary and meets_min_distance:
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if in_flex and meets_min_distance:
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current_period.append(
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{
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"interval_hour": starts_at.hour,
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@ -26,12 +26,15 @@ The integration automatically calculates **Best Price Periods** (cheap time wind
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### Basic Principle
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The calculation happens in **two main steps**:
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The calculation happens in **multiple steps**:
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1. **Period Identification**: Find contiguous time ranges that differ significantly from the daily average
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2. **Filter Application**: Apply various filters to keep only relevant periods
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1. **Period Identification**: Find contiguous time ranges within a **flexibility range** of the daily MIN/MAX prices
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2. **Hard Filters**: Apply non-configurable filters (periods must be below/above average)
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3. **Length Filter**: Remove periods that are too short
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4. **Quality Filter**: Ensure meaningful distance from average
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5. **Optional Filters**: Apply volatility and level filters if configured
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Both steps can be influenced by configuration options.
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All steps except #2 can be influenced by configuration options.
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---
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@ -41,39 +44,50 @@ Both steps can be influenced by configuration options.
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**What happens:**
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- Fetch all price intervals for today (96 x 15-minute intervals = 24 hours)
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- Calculate daily average price
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- Calculate daily **MIN, MAX, and AVG** prices
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- Calculate trailing 24h average for each interval
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**Example:**
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```
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Today: 96 intervals from 00:00 to 23:59
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Average price today: 25.5 ct/kWh
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Daily MIN: 18.0 ct/kWh
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Daily MAX: 35.0 ct/kWh
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Daily AVG: 26.5 ct/kWh
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```
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### Step 2: Period Identification (Flexibility)
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**What happens:**
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- Search for contiguous intervals that are **significantly cheaper** (Best Price) or **more expensive** (Peak Price) than the average
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- "Significant" is defined by the **flexibility** setting
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- Search for contiguous intervals within a **flexibility range** of the daily extreme prices
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- **Best Price**: Includes intervals within flexibility range of the day's **MINIMUM** price
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- **Peak Price**: Includes intervals within flexibility range of the day's **MAXIMUM** price
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**Configuration:**
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- `best_price_flex` (default: 15%) - How much cheaper than average?
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- `peak_price_flex` (default: -15%) - How much more expensive than average?
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- `best_price_flex` (default: 15%) - How much more expensive than the daily MIN can an interval be?
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- `peak_price_flex` (default: -15%) - How much less expensive than the daily MAX can an interval be?
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**Example (Best Price with 15% flexibility):**
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```
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Average price: 25.0 ct/kWh
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Flexibility: -15%
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Threshold: 25.0 - (25.0 × 0.15) = 21.25 ct/kWh
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Daily prices: 18.0 ct (min), 35.0 ct (max), 26.5 ct (avg)
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Flexibility: 15%
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Reference: Daily MIN = 18.0 ct (not average!)
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Threshold: 18.0 + (18.0 × 0.15) = 20.7 ct/kWh
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Intervals that cost ≤ 21.25 ct/kWh are grouped into periods:
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00:00-00:15: 20.5 ct ✓ │
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00:15-00:30: 19.8 ct ✓ ├─ Period 1 (1h)
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00:30-00:45: 21.0 ct ✓ │
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Intervals that cost ≤ 20.7 ct/kWh are grouped into periods:
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00:00-00:15: 18.5 ct ✓ │
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00:15-00:30: 18.0 ct ✓ ├─ Period 1 (1h)
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00:30-00:45: 19.8 ct ✓ │
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00:45-01:00: 20.2 ct ✓ │
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01:00-01:15: 26.5 ct ✗ (too expensive, period ends)
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01:00-01:15: 21.5 ct ✗ (exceeds flexibility threshold, period ends)
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```
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**Why compare to MIN/MAX instead of average?**
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- Creates periods around the **best/worst price opportunities** of the day
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- More predictable behavior: flexibility directly controls how far from the extreme prices you go
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- Prevents marking mediocre prices as "best" just because the daily average is high
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**Note:** The flexibility check (vs MIN/MAX) and the minimum distance check (vs AVG in Step 4) work together to ensure periods are both close to extremes AND meaningfully different from average.
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### Step 3: Minimum Period Length
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**What happens:**
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@ -94,29 +108,49 @@ Found periods:
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### Step 4: Minimum Distance from Average
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**What happens:**
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- Periods must have **additional** distance from the daily average beyond flexibility
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- This is a **SEPARATE** filter from flexibility (Step 2)
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- Each interval must be sufficiently far from the daily average
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- Prevents marking "almost normal" prices as "Best/Peak" on days with small price spread
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- **Implicitly ensures intervals are below/above average** (since distance > 0% by default)
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**Configuration:**
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- `best_price_min_distance_from_avg` (default: 2%) - Additional distance below average
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- `peak_price_min_distance_from_avg` (default: 2%) - Additional distance above average
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- `best_price_min_distance_from_avg` (default: 2%) - Minimum distance below average
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- `peak_price_min_distance_from_avg` (default: 2%) - Minimum distance above average
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**Example (Best Price):**
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```
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Daily average: 25.0 ct/kWh
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Flexibility threshold: 21.25 ct/kWh (from Step 2)
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Daily prices: 18.0 ct (min), 35.0 ct (max), 26.5 ct (avg)
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Flexibility: 15%
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Minimum distance: 2%
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Final check for each interval:
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1. Price ≤ flexibility threshold? (21.25 ct)
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2. AND price ≤ average × (1 - 0.02)? (24.5 ct)
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Flexibility threshold (from Step 2): 18.0 × 1.15 = 20.7 ct
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Average distance threshold: 26.5 × 0.98 = 25.97 ct
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Interval with 23.0 ct:
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✗ Meets flexibility (23.0 > 21.25)
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✓ Meets minimum distance (23.0 < 24.5)
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→ REJECTED (both conditions must be met)
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Final check for each interval - BOTH conditions must pass:
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1. Price ≤ flexibility threshold? (20.7 ct) ← vs MIN
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2. AND price ≤ average distance threshold? (25.97 ct) ← vs AVG
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Interval at 19.5 ct:
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✓ Meets flexibility (19.5 ≤ 20.7)
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✓ Meets min distance (19.5 ≤ 25.97)
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→ ACCEPTED (both conditions met)
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Interval at 22.0 ct:
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✗ Fails flexibility (22.0 > 20.7)
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✓ Meets min distance (22.0 ≤ 25.97)
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→ REJECTED (flexibility condition failed)
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Interval at 26.0 ct (hypothetical):
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✗ Fails flexibility (26.0 > 20.7)
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✗ Fails min distance (26.0 > 25.97)
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→ REJECTED (both conditions failed)
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```
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**Why this matters:**
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- On days with small price variation, flexibility alone might include intervals that are barely below average
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- The minimum distance filter ensures you're actually getting meaningful savings
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- With default 2%, intervals must be at least 2% below average (which also ensures they're below average)
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### Step 5: Filter Application
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**What happens:**
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@ -131,9 +165,9 @@ Interval with 23.0 ct:
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| Option | Default | Description | Acts in Step |
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|--------|---------|-------------|--------------|
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| `best_price_flex` | 15% | How much cheaper than average must a period be? | 2 (Identification) |
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| `best_price_flex` | 15% | How much more expensive than the daily **MIN** can an interval be? | 2 (Identification) |
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| `best_price_min_period_length` | 60 min | Minimum length of a period | 3 (Length filter) |
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| `best_price_min_distance_from_avg` | 2% | Additional minimum distance below daily average | 4 (Quality filter) |
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| `best_price_min_distance_from_avg` | 2% | Minimum distance below daily **average** (separate from flexibility) | 4 (Quality filter) |
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| `best_price_min_volatility` | LOW | Minimum volatility within the period (optional) | 5 (Volatility filter) |
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| `best_price_max_level` | ANY | Maximum price level (optional, e.g., only CHEAP or better) | 5 (Level filter) |
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| `best_price_max_level_gap_count` | 0 | Tolerance for level deviations (see [Gap Tolerance](#gap-tolerance-for-level-filters)) | 5 (Level filter) |
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@ -145,9 +179,9 @@ Interval with 23.0 ct:
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| Option | Default | Description | Acts in Step |
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|--------|---------|-------------|--------------|
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| `peak_price_flex` | -15% | How much more expensive than average must a period be? | 2 (Identification) |
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| `peak_price_flex` | -15% | How much less expensive than the daily **MAX** can an interval be? | 2 (Identification) |
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| `peak_price_min_period_length` | 60 min | Minimum length of a period | 3 (Length filter) |
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| `peak_price_min_distance_from_avg` | 2% | Additional minimum distance above daily average | 4 (Quality filter) |
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| `peak_price_min_distance_from_avg` | 2% | Minimum distance above daily **average** (separate from flexibility) | 4 (Quality filter) |
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| `peak_price_min_volatility` | LOW | Minimum volatility within the period (optional) | 5 (Volatility filter) |
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| `peak_price_min_level` | ANY | Minimum price level (optional, e.g., only EXPENSIVE or higher) | 5 (Level filter) |
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| `peak_price_max_level_gap_count` | 0 | Tolerance for level deviations (see [Gap Tolerance](#gap-tolerance-for-level-filters)) | 5 (Level filter) |
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@ -396,6 +430,8 @@ Step 3: ...
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**Calculation:** `new_flexibility = old_flexibility × (1 + relaxation_step / 100)`
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**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.
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#### Level 2: Disable Volatility Filter
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```
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If flexibility relaxation isn't enough:
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@ -463,23 +499,26 @@ best_price_max_level: "any" # Filter disabled
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**Daily prices:**
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```
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Average: 25.0 ct/kWh
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00:00-02:00: 19-21 ct (cheap)
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MIN: 18.0 ct/kWh
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MAX: 32.0 ct/kWh
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AVG: 25.0 ct/kWh
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00:00-02:00: 18-20 ct (cheap)
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06:00-08:00: 28-30 ct (expensive)
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12:00-14:00: 24-26 ct (normal)
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18:00-20:00: 20-22 ct (cheap)
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18:00-20:00: 19-21 ct (cheap)
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```
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**Calculation:**
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1. Flexibility threshold: 25.0 - (25.0 × 0.15) = 21.25 ct
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2. Minimum distance threshold: 25.0 × (1 - 0.02) = 24.5 ct
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3. Both conditions: Price ≤ 21.25 ct
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1. Flexibility threshold: 18.0 × 1.15 = 20.7 ct (vs MIN, not average!)
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2. Minimum distance threshold: 25.0 × 0.98 = 24.5 ct (vs AVG)
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3. Both conditions: Price ≤ 20.7 ct AND Price ≤ 24.5 ct
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**Result:**
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- ✓ 00:00-02:00 (19-21 ct, all ≤ 21.25)
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- ✓ 00:00-02:00 (18-20 ct, all ≤ 20.7 and all ≤ 24.5)
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- ✗ 06:00-08:00 (too expensive)
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- ✗ 12:00-14:00 (24-26 ct, not cheap enough)
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- ✓ 18:00-20:00 (20-22 ct, all ≤ 21.25)
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- ✗ 12:00-14:00 (24-26 ct, exceeds flexibility threshold of 20.7 ct)
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- ✓ 18:00-20:00 (19-21 ct, all ≤ 20.7 and all ≤ 24.5)
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**2 Best Price periods found!**
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@ -572,40 +611,42 @@ enable_min_periods_best: true
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min_periods_best: 2
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relaxation_step_best: 25
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best_price_flex: 10 # Very strict!
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best_price_flex: 5 # Very strict!
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best_price_min_volatility: "high" # Very strict!
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```
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**Day with little price spread:**
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```
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Average: 25.0 ct/kWh
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MIN: 23.0 ct/kWh
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MAX: 27.0 ct/kWh
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AVG: 25.0 ct/kWh
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All prices between 23-27 ct (low volatility)
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```
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**Relaxation process:**
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1. **Attempt 1:** 10% flex + HIGH volatility
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1. **Attempt 1:** 5% flex + HIGH volatility
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```
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Threshold: 22.5 ct
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Threshold: 23.0 × 1.05 = 24.15 ct (vs MIN)
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No period meets both conditions
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→ 0 periods (< 2 required)
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```
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2. **Attempt 2:** 12.5% flex + HIGH volatility
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2. **Attempt 2:** 6.25% flex + HIGH volatility
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```
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Threshold: 21.875 ct
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Threshold: 23.0 × 1.0625 = 24.44 ct
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Still 0 periods
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```
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3. **Attempt 3:** Disable volatility filter
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```
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12.5% flex + ANY volatility
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6.25% flex + ANY volatility
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→ 1 period found (< 2)
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```
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4. **Attempt 4:** 15.625% flex + ANY volatility
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4. **Attempt 4:** 7.81% flex + ANY volatility
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```
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Threshold: 21.09 ct
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Threshold: 23.0 × 1.0781 = 24.80 ct
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→ 2 periods found ✓
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```
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@ -623,7 +664,7 @@ All prices between 23-27 ct (low volatility)
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1. **Too strict flexibility**
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```
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best_price_flex: 5 # Only 5% cheaper than average
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best_price_flex: 5 # Only allows intervals ≤5% above daily MIN
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```
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**Solution:** Increase to 10-15%
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@ -648,7 +689,7 @@ All prices between 23-27 ct (low volatility)
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5. **Day with very small price spread**
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```
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All prices between 24-26 ct (hardly any differences)
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MIN: 23 ct, MAX: 27 ct (hardly any differences)
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```
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**Solution:** Enable relaxation mechanism:
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```yaml
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