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Understanding Power Charts

The stromleser app shows your consumption data in various charts. Here you'll learn how to correctly interpret these charts and what they reveal to you.

Chart Types

Bar Charts

Most commonly used

Bar charts show discrete values for specific time periods:

  • Each bar = one time segment (hour, day, month)
  • Height of bar = consumption in that period
  • Different colors = different categories (consumption, feed-in)

Line Charts

For trends and progressions

Line charts show continuous values:

  • Each point = one measurement time
  • Line connects the points
  • Ideal for current power over time

Pie Charts

For shares and distributions

Show proportions:

  • Total circle = 100%
  • Each segment = share of whole
  • E.g., HT/NT distribution, self-consumption vs. grid consumption

Understanding Time Levels

Hourly View

Last 24 hours in detail

What do you see?

  • 24 bars, one per hour
  • Current hour not yet complete
  • Shows consumption patterns of day

How to interpret?

Example:
00:00-01:00: 0.3 kWh → Low night consumption
06:00-07:00: 1.2 kWh → Morning peak (coffee, breakfast)
12:00-13:00: 0.8 kWh → Lunch
18:00-19:00: 2.1 kWh → Evening peak (cooking, multiple devices)
22:00-23:00: 0.4 kWh → Evening, little activity

What can you learn from it?

  • When do you consume most?
  • Are there unexpected peaks?
  • Are devices running when nobody's home?
Tip

Look at hourly view on different weekdays. Do you recognize patterns?

Daily View

Last 7-30 days overview

What do you see?

  • One bar per day
  • Total daily consumption in kWh
  • Comparison between days

How to interpret?

Example:
Mon: 12.5 kWh → Normal workday
Tue: 11.8 kWh → Normal workday
Wed: 13.2 kWh → Slightly higher (home office?)
Thu: 12.1 kWh → Normal
Fri: 14.5 kWh → Higher (long dinner?)
Sat: 18.3 kWh → Significantly higher (at home, many activities)
Sun: 16.7 kWh → Higher than weekday

What can you learn from it?

  • Weekend vs. weekday patterns
  • Consumption on work-from-home days
  • Particularly consumption-intensive days

Typical patterns:

Normal household:

  • Weekdays: 10-15 kWh/day
  • Weekend: 15-20 kWh/day
  • Reason: More at home on weekends

Household with home office:

  • Relatively even: 12-16 kWh/day
  • No big difference between weekdays

Household with PV system:

  • Sunny days: Low grid consumption or negative (feed-in)
  • Cloudy days: Higher grid consumption

Monthly View

Last 12 months in annual comparison

What do you see?

  • One bar per month
  • Total monthly consumption in kWh
  • Seasonal fluctuations

How to interpret?

Example:
Jan: 450 kWh → High (winter, lots of light, heating pump)
Feb: 420 kWh → High (winter)
Mar: 380 kWh → Decreasing (days getting longer)
Apr: 320 kWh → Medium (spring)
May: 280 kWh → Low (summer approaching)
Jun: 250 kWh → Low (summer)
Jul: 240 kWh → Low (summer)
Aug: 260 kWh → Low (summer)
Sep: 300 kWh → Increasing (autumn)
Oct: 350 kWh → Medium (autumn)
Nov: 410 kWh → High (darker days)
Dec: 470 kWh → High (winter, holidays)

What can you learn from it?

  • Seasonal fluctuations
  • Project annual consumption
  • Trends over multiple years

Typical seasonal effects:

Winter (Nov-Feb):

  • Highest consumption
  • Reason: Lots of light, heating pump runs more often

Summer (May-Aug):

  • Lowest consumption
  • Reason: Little light, lower heating demand

Spring/Autumn:

  • Medium consumption
  • Transition periods

PV-Specific Charts

If you have a photovoltaic system, you'll see extended charts.

Consumption vs. Feed-in

Two bars or areas

  • Green area: Grid consumption
  • Blue area: Grid feed-in

Interpretation:

Example summer day:
00:00-06:00: Consumption (no sunlight)
06:00-10:00: Decreasing consumption (PV starts)
10:00-15:00: Feed-in (PV surplus)
15:00-18:00: Low consumption (PV still running)
18:00-24:00: Consumption (no sunlight)

Ideal daily progression (summer):

  • Night: Minimal consumption (only standby)
  • Morning: PV covers consumption
  • Noon: PV surplus → Feed-in
  • Evening: Low consumption for cooking
  • Night: Minimal consumption

Self-Sufficiency Chart

Pie chart or percentage display

Shows how much of your consumption is covered by your own PV production.

Interpretation:

  • 0-20%: Very low self-consumption

    • Possible reasons: Small PV system, high consumption, winter
  • 20-40%: Low self-consumption

    • Typical for small systems without battery
  • 40-70%: Good self-consumption

    • Typical for well-sized systems in summer
  • 70-90%: Very good self-consumption

    • With battery and optimized consumption behavior
  • 90-100%: Nearly self-sufficient

    • Only possible with large battery

Optimization:

To increase self-sufficiency rate:

  1. Consume electricity during day when PV produces
  2. Use timer functions for washing machine, dishwasher
  3. Charge e-cars during day
  4. Consider battery storage

Self-Consumption Rate

How much PV electricity do you use yourself?

Self-consumption rate = Self-consumption / PV production × 100%

Interpretation:

  • 0-30%: Low self-consumption

    • Lots of feed-in, little self-use
    • Consumption mainly evenings/nights
  • 30-50%: Medium self-consumption

    • Typical without battery storage
  • 50-80%: High self-consumption

    • Good load shifting or battery
  • 80-100%: Very high self-consumption

    • Large battery storage or high daytime consumption

Cost Charts

If you configured tariffs, you'll also see cost charts.

Daily Costs

How much does each day cost you?

Example:
Mon: €4.20 → Normal day
Tue: €3.85 → Slightly lower
Wed: €5.50 → Higher (more cooking, home office)
Thu: €4.10 → Normal
Fri: €4.80 → Slightly increased
Sat: €6.20 → Weekend, more at home
Sun: €5.90 → Weekend

What do you recognize?

  • Most expensive days of month
  • Potential for savings
  • Effects of behavior changes

Monthly Costs with Trend

Projection to end of month

The app shows you:

  • Costs to date (e.g., after 15 days)
  • Projection for entire month
  • Comparison to previous month
Example (15th of month):
Costs to date: €62.50
Projection: ~€125
Last month: €118
→ Slightly higher than last month

Interpretation Tips

Finding Consumption Peaks

How to find outliers?

  1. Look at daily view
  2. Search for particularly high bars
  3. Think: What was different on that day?
  4. Switch to hourly view of that day
  5. Find specific hour with high consumption

Example:

Daily view: Saturday 25 kWh (normal: 15 kWh)
→ Hourly view: 14:00-16:00 particularly high
→ Memory: Oven 2 hours for cake

Is your consumption rising or falling?

  1. Open monthly view
  2. Look at last 6-12 months
  3. Watch for tendency up or down

Positive trends (falling):

  • LED bulbs installed
  • Old devices replaced
  • More conscious behavior

Negative trends (rising):

  • More home office
  • New devices (aquarium, server, etc.)
  • Changed habits

Making Comparisons

How to compare effectively?

Compare same weekdays:

Mon this week: 12.5 kWh
Mon last week: 11.8 kWh
Mon 2 weeks ago: 12.1 kWh
→ Quite consistent

Months in annual comparison:

January 2025: 450 kWh
January 2024: 480 kWh
→ 30 kWh savings, good!

Recognizing Anomalies

Unexpectedly High Consumption

What could be reasons?

  1. Device Running Continuously

    • Freezer door not properly closed
    • Heating accidentally left on
    • Device defective and drawing continuous power
  2. Special Events

    • Visitors/guests
    • Party
    • Intensive cooking days (canning, baking)
  3. Seasonal Effects

    • First cold snap
    • Heating pump runs more

Unexpectedly Low Consumption

Also interesting!

  1. Absence

    • Vacation
    • Business trip
    • Weekend getaway
  2. Technical Problem

    • Device not working (refrigerator?)
    • Wi-Fi outage → no data transmission
    • Device disconnected from power

Frequently Asked Questions

Why are some bars incomplete?

Current hour/day/month is not yet complete. Bar grows over time.

Can bars be negative?

Yes, with PV systems! A negative value means feed-in (more produced than consumed).

Why do values fluctuate so much?

This is normal! Your consumption constantly changes depending on which devices are running.

How accurate are projections?

Projections are based on consumption to date. They are estimates and may vary, especially at beginning of month.

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