In Germany:
From an annual consumption of more than 100,000 kWh, customers are generally billed using registered power metering (RLM).
This means:
your metering point operator or grid operator records your power consumption at 15-minute intervals
these values form your load profile - your actual power draw over time
as an RLM customer you can request this data and typically receive it as a file
These load profiles are the foundation of our battery sizing.
To work with facts rather than assumptions, we combine several data sources in our own software:
1. Load profiles (RLM data)
15-minute data over at least 12 months
actual annual peak loads and load spikes
typical daily, weekly and seasonal patterns
2. Power prices and grid fees
current and planned power supply contracts
energy charges, demand charges, grid fees
special cases such as high load time windows or atypical grid usage
3. Generation and grid connection data
PV or CHP generation
import and export at the grid connection point
voltage level and technical boundary conditions
4. Looking ahead
changes in production or shifts
new assets, additional loads, electrification
site strategy (growth, consolidation)
Step 1 - Data intake and quality check
As soon as we have your data:
we import load profiles and tariff data
we check completeness and plausibility
we clean up measurement errors and outliers
Step 2 - Simulation of many battery and use case combinations
Our software then simulates for your site:
different battery sizes (power and capacity)
different operating strategies, e.g.
peak shaving
reduction of demand charges and grid fees
combination with PV self-consumption
different price and regulatory scenarios
The goal is not a “theoretical optimum”, but a solution that is technically realistic and operable in day-to-day business.
Step 3 - Selection based on payback and robustness
For each variant we calculate, among other things:
investment and operating costs
annual savings
expected payback period
sensitivity to changes in power prices and usage patterns
From this portfolio we identify the battery solution that
has a realistic payback period,
delivers robust savings and
fits your site strategy.
An industrial battery can serve several purposes at the same time:
peak shaving
reduction of demand charges and grid fees
use of low-price hours
integration of on-site generation
We simulate different multi-use profiles instead of looking only at an isolated peak shaving case. This leads to sizing that is close to the real payback and avoids ending up with a “nice to have” battery without a clear business case.
Once we have your data in full, the process typically looks like this:
Day 1
data import, quality check, definition of boundary parameters
Day 2
simulation of battery and use case combinations, economic evaluation
Day 3
preparation of results, derivation of a clear recommendation
No later than 3 working days after receiving your data we can present and discuss the results with you.
In the results presentation you receive, among other things:
1–2 concrete recommended battery sizes (power and capacity)
expected payback period and annual savings potential
overview of the most relevant use case combinations
sensitivity of the results to changing boundary conditions
technical key data as a basis for further planning and offers
The goal is a robust decision basis: