The Lynus Energy Management System (EMS) is one of the most comprehensive tools in our library.
This makes it possible to get different electrical consumers and generators in the building on one control level.
The EMS works with the following data:
Thus, Lynus' EMS knows exactly how the consumption and generation of the devices in the building will behave in the future and, thanks to this knowledge, can incorporate various schedules and controls back into the real-time system on site.
These historical as well as future data, the so-called predictions, are visible to the customer in various ways and can be retrieved at any time.
These include:
Thus, degrees of self-sufficiency of up to almost 100% can be achieved. Self-consumption in the building is increased and CO2 emissions are reduced.
Lynus EMS can be connected to various devices on the generation or consumption side and thus also controlled or regulated.
The most common ones include:
When it comes to the topic of e-cartridges (heating inserts) in hot water storage tanks, the topic of Legionella also comes up. Most conventional legionella protection circuits simply switch on at some point during the day to heat the storage tank to the necessary temperature. This usually involves the use of expensive mains electricity.
With the control of the heating insert by Lynus and its EMS, this heating phase is shifted to the time when there is surplus energy in the building. This saves the operation with expensive mains electricity and at the same time the issue of legionella is taken care of with the specially generated energy. If nevertheless once not enough surplus energy is available, the Legionella circuit is executed 1 times weekly.
Each consumer can be linked to a prioritization in the EMS.
Thus, for example, devices with high prioritization are supplied with surplus energy first. Consumers with low prioritization are supplied later. In addition to prioritization, other criteria and setting options can be specified for the loads.
These include
In order to control the consumers in general, the EMS offers various ways of working:
Properties in operation self-consumption optimization:
Characteristics in peak load shaving operation:
Properties in operation load management:
The influence of machine learning can also be adapted and regulated on a project-specific basis. Thus, it is possible, for example, to allocate battery capacities differently, or to switch on heat pumps at more optimal times.
The machine learning part can be operated in the following modes:
General Notice:
Certain system-relevant commands are generally executed on the real-time system.
Without machine learning, a classic EMS reacts only to the actual state of the plant.
The sequence on the graph at "Today" can be briefly described as follows:
The sequence on the graph at "Tomorrow" can be briefly described as follows:
The sequence on the graph at "The day after tomorrow" can be briefly described as follows:
Lynus energy management responds to both the actual state of the plant, as well as future data, using various machine learning algorithms internally.
The sequence on the graph at "Today" can be briefly described as follows:
The sequence on the graph at "Tomorrow" can be briefly described as follows:
The sequence on the graph at "The day after tomorrow" can be briefly described as follows:
-20%
Less energy consumption-25%
less CO2 emissions+30%
more own power consumption