A Way Towards Smart Grid

Smart Control Based on Dynamic Prices from the Market

Feramat Cybernetics together with the progressive energy distributor Nano Energies offers a system for a cost-saving control of big electrical appliances, where energy consumption could be delayed during a day (i.e. load shifting or demand side management).


The price of commodity is constant but at least 10% lower than a common price.
This type of the system operation stabilizes a distribution net.
More flexibility in the load shifting means more savings.

Idea Behind

The consumption reflects the situation on the intraday electricity market.
Cloud–based control system ensures fulfilment of the customer requests.
Control system can be also used in a reversed mode for a flexible energy production.

Parameters and Requirements

A circuit breaker bigger than 3×100 A
Electricity measurement of type A or B
Consumption of the energy can be max 10 hours per day (anytime)
Electricity distributor is
Nano Energies Trade s.r.o.

The Smart control is suitable for heating/cooling systems in buildings or industrial processes where the heat/cool is prepared by the electrical energy (e.g. heat pumps) and is stored in some type of an accumulation.

The application of this control system is not limited on the HVAC but it can be used in many different areas.

Case Study


The heat pump is controlled to have enough warm water in the accumulation tank and also to produce warm water mainly in the moments of cheap electrical energy on the intraday market. The priority is the heat comfort in the zone – these comfort requests must be always fulfilled. A static model of the heat consumption and a thermodynamic model are necessary to plan the heat production.

Savings are dependent on parameters of the accumulation tank, the heat pump and a behavior of the building. For more information and savings calculation contact us.


Algorithms for a Consumption Distribution in Time in Case of Quarter–hour Maximum Limits

MPC is a perfect mean for regulating the quarter–hour energy consumption, because the controller foresees the predicted energy consumption and knows the power limits and thus it optimizes the consumption profile in order to satisfy the consumption limits. Therefore the end customer saves not only on the costs for the commodity, but also on the costs for reserved capacity.

The predictive control is able to plan the consumption of the energy to meet the limits, thanks to the mathematical model. This type of the regulation is suitable for systems with slow dynamics e.g. systems with accumulation (batteries, accumulation water tanks, TABS systems etc.). The model is also possible to use for the proper determination of reserved power capacity.

A typical problem which cannot be solved by classical control algorithms is to meet energy consumption limits and temperature setpoints in different heating zones. The Smart control based on predictive algorithms (MPC) is the right solution for this problem.

Case Study

There are three heating zones connected to one heat exchanger and there also exists a power consumption limit (i.e. a quarter-hour maximum). A traditional control system is not able to solve this problem (without some penalties for an overconsumption) – it can only contain some heuristic rules which do not ensure meeting of the consumption limits.

The predictive Smart control is able to have the consumption under the limit and fulfil the temperature setpoints (i.e. heat comfort) in all zones in time.

The figure shows a situation, when a change of the setpoint is coming after the Christmas. The predictive controller plans to start the heat supply two days before the change of the setpoint and as can be seen from the graph, the consumption limit was always under the limit. Traditional control system would not meet the temperature setpoint or would break the consumption limit.