Show what is possible behind the meter with an anticipating EMS
We can buy modern energy assets, but what asset sizes can actually work well?
How efficient can we operate them, while ensuring we operate within limits?
Imagine being able to present the definite answer, even for complex settings.
With our state-of-the-art simulations, you can help your customers decide what assets to invest in. We run multiple scenarios in highly realistic fashion. Intelligent timing of energy usage often makes a sizable difference.
Modern assets like solar, EVs, heat pumps and batteries make your sites future-ready, but they also can cause trouble when they do not act well in orchestration.
The three major goals we identify are:
Stay within grid capacity limits
Reduce energy costs
Become greener / increase self-consumption
For each site, we simulate a full-year of data-driven dynamic energy orchestration, under realistic circumstances. Each optimal schedule is made based on uncertain knowledge of what the day will be like. Excel spreadsheets cannot capture this realism.
And when a scenario is chose, we can help run it optimally in real-time
Features
The building consumption data forms the basis
Plan solar expansion
Use dynamic EPEX tariffs
Simulate occupancy on your EV charging stations
See how a battery helps you to stay within limited grid connection* and save on energy costs
Build multiple future scenarios, e.g. effect of extra solar, small and large battery
Compare these scenarios and make their effects clear on a KPI page
Dive into the simulation data in interactive plots
* We have modeled temporary expanded capacity (like Capaciteits-beperkende contracten) and peak-avoidance reward programs (BeatThePeak).
** For EV charging, we have modeled HBE certificates (Hernieuwbare Brandstof Eenheden)
Example case: Provinciehuis Flevoland
A large public office building in Lelystad (province Flevoland) in The Netherlands. The owners want to run it more sustainable and to understand if more solar panels would be helpful. Now they have 16 EV chargers, which should become more in the future. Grid congestion might become a problem, so they want to make sure it is unlikely to happen. Finally, they want to give an innovative example to the market.
We simulated several scenarios and showed that a smaller battery (100kWh) seems like a good choice and that smart charging can help the building.
With the data deep-dive that lets you travel through time, the actual predictions and behavior becomes clear
How does it work?
Per case, you fill in a sheet with data and the scenarios we should simulate. The results (KPIs, detailed totals and the ability to deep-dive) will be ready within two business days.
This is a complex service, and only a win-win in the long-run if we establish a collaboration. We are offering our channel partners the following journey: It’s easy to try our Seita Simulation service in a pilot case, after which we work together on on-boarding, to ensure efficient handling of new cases at scale.
1. Pilot Case
Discuss 1st case & scenarios
2 Iterations on case sheet
Computation
Outcomes & KPIs review
2. Workshop (2h)
How to fill in case sheets
How to choose scenarios
Discussing results & KPIs
Deep diving into data
3. Account Setup
2 users included
Each client gets read access
4. Add New Cases
4 scenarios (incl baseline)
Results within 4 biz days
KPI page
Data deep-dive
Raw data export
Book a Demo
A 30 minute demonstration of our simulation service in an example case, plus a short discussion of your ideas
