Peak load management - how industry and companies can avoid peak loads

Why is dynamic load management so important in industry? Is it worth using an intelligent load control system to reduce peak loads?

As peak loads often cause high costs at the end of the year, it is important to reduce or avoid peak loads (also known aspeak shaving ). We offer you the right solution and accompany you on the path to cost savings and greater energy efficiency.

First of all, we would like to refresh your knowledge and explain what a peak load is and how peak shaving works.

How does a peak load occur?

In the case of companies and industrial operations that draw more than 100,000 kWh of electricity per year, the power (kW) is usually measured and billed by the grid operator in addition to the amount of energy (kWh). This takes into account the increased load on the supply grid above a certain power consumption. As electricity prices continue to rise, load management is becoming increasingly important for many companies.

In a normal tariff, payment for the power purchased is based on the annual peak load, the highest load within 15 minutes (peak load) that has occurred in a year. This value is overwritten in the peak load memory of the meter at the transfer point with the last highest 15-minute load and reset at the beginning of each month. The monthly electricity peak can thus be read from the peak load memory at the end of each month.

Peak load storage of a meter at the transfer point.

The value of the memory is overwritten monotonically increasing with the last 15-minute load if this was higher than the previous value.

The actual power curve (resolution in the graphic here: 15 seconds) and how this is averaged over the 15-minute time window of the peak load storage are therefore decisive for the occurrence of a new power peak. This means that a new load peak occurs as soon as the integral under the active power is greater than the integral under the value of the peak load storage within a 15-minute interval. This corresponds to the comparison of the active energy drawn in each new 15-minute interval with the maximum active energy drawn in such an interval. A temporal shift in the actual power curve during the time windows therefore has a major influence on the value of the 15-minute load. In addition, power levels may well be higher than the peak load without this leading directly to an increase in the peak load.

Accurate data acquisition with real-time data, such as with the ENIT agent, is therefore also essential for detecting peak loads and is the basic building block for advanced energy management. In order to keep the peak load as low as possible and thus save costs, it is worth taking a closer look at the consumers responsible and then optimizing the process: You can find out how peak load capping or reduction works and what interventions are possible via intelligent load management in our load management knowledge area.