Table of contents

• Setpoint
• Optimization of energy costs
  • 1. Storage
  • 2. Variable power loads (EVs, ...)
  • 3. PV Production
• Optimization of self consumption
  • 1. Fixed power devices (heat pumps, ...)
  • 2. Variable power loads (EVs, ...)
  • 3. Storage
• Feed-in restriction
• Peak shaving only
  • 1. Storage
  • 2. Variable power loads (EVs, ...)
• External signal
• Uncontrolled

More about the algorithms behind the control modes is only available on request due to the protection of intellectual property.

Setpoint

By utilizing the Setpoint mode, the system ensures that critical energy devices can operate at their full capacity without compromising the overall power supply. This mode guarantees the delivery of the required power unless it conflicts with higher-priority devices. It allows for efficient and reliable energy management, preventing potential disruptions while optimizing energy usage.

For example, consider a DC charger that needs to consistently deliver 100 kW, unless the energy meter at the installation's main connection indicates that the maximum power draw would be exceeded. In this scenario, the DC charger is assigned priority 2, while the energy meter is assigned priority 1.

Optimization of energy costs

The "Energy Cost Optimization" mode takes into account the energy market relevant to the customer. It analyzes periods of low and high energy costs, and based on this information, adjusts energy technologies and their consumption or production accordingly. This mode may restrict production, store energy, or increase/decrease consumption, depending on the time intervals identified as economically favorable. The goal is to make the most cost-effective decisions.

1. Storage

Several factors are considered when determining the optimal strategy. These include battery charging cycles, compressor start and stop schedules, and the feed-in tariff for solar energy. At certain times, energy prices may even become negative, and the smart grid controller takes advantage of such situations.

The optimization algorithm looks for the most optimal path of the amount of stored energy over time to optimize cost. You may see the following things happen:

General behavior:

• Most optimal charge moment: The most optimal moment for the battery to charge generally is when there is excess PV generation available at the moment of the day when the sell price of energy is the lowest. This tends to be in the afternoon.
• Most optimal discharge moment: The most optimal moment for the battery to discharge generally is when there is energy consumption at the moment of the day when the buy price of energy is the highest. This tends to be at night.
• Amount of charge: The battery will only charge as much energy as the algorithm estimates that is needed or could give a financial benefit when discharging later for selling to the grid.

Other moments of discharging:

• If there is more energy available in the battery than required by the consumption and the energy was charged at a price low enough compared to the current energy price to overcome the degradation cost of the battery, then the battery may discharge to sell energy to the grid at a profit. This corresponds for example to selling excess PV energy at a later moment, when energy prices are higher.

Other moments of charging:

• If there is no excess PV energy available and energy prices are very low, then the battery may charge.

2. Variable power loads (EVs, ...)

The charging will happen at the moments that the energy prices are the lowest.

3. PV Production

PV production will be reduced to not have export to the grid at moments that prices are negative.

Optimization of self consumption

With this control mode, the controller will try to match the consumption as good as possible with the the local production. A different approach is used based on the type of device, in the order given below.

1. Fixed power devices (heat pumps, ...)

For these devices, the controller will estimate how much time the device needs to be on to fullfill its energy needs. The device is scheduled to switch on (or be given a smart grid control signal) at the moment when there is enough excess energy available during a long enough time period.

2. Variable power loads (EVs, ...)

In the case of variable power loads, the controller will distribute the available excess energy over all the variable power loads as evenly as possible using the "democratic charging" algorithm. If all the available excess energy has been allocated already and not all EVs have their energy demand completely met, the remaining required energy will be scheduled to take place immediately at the maximum current possible.

3. Storage

Any remaining energy will be stored for later use. Later when there is not enough production available to supply all loads, the storage will discharge first to supply to these loads.

Feed-in restriction

The feed-in restriction mode only applies to PV production. With this mode, the PV production will be reduced so that there is no net export to the grid (feed in restrictions). This mode is always applied after all other modes, to make as best use as possible of available PV production.

Peak shaving only

With this mode, the controller will try to reduce peaks as much as possible. A different approach is used based on the type of device, in the order given below.

1. Storage

Storage will discharge at the highest import powers and charge at the highest export powers, to smooth out the peaks as much as possible.

2. Variable power loads (EVs, ...)

In this mode the controller will distribute the available grid capacity over all the variable power loads as evenly as possible, using the "democratic charging" algorithm.

External signal

It is possible to add an external signal to variably change the used control mode. Please contact Eniris for more possible integrations.

Uncontrolled

This disables the control of the device in question.