Improving step-by-step the energy efficiency in industrial refrigeration systems can lead to great financial benefits and improvements of environmental outcomes for your company.
If a complete refrigeration upgrade cannot be achieved, improve the efficiency of an existing system with small alterations, low-cost maintenance practices and system changes is the only solution.
Potential savings and energy efficiency of an industrial refrigeration system are difficult to be measured because can vary dependent on outside temperature and refrigerator load. This is the reason many companies are most of the time negative to try system changes or to install energy saving equipment such as frequency drives, electronic controllers and automatic controlled valves.
In order to measure the energy efficiency improvements you’ll need except the existing temperature and pressure logging system, to install at least two energy consumption meters, one on the compressors and one on the rest of the equipment (ventilators, condensers etc.) and a real-time energy price API feed.
While the traditional ESCOs promising rainbows and unicorns trying to calculate the COP (Coefficient of Performance) and the EER (energy efficiency ratio) using handbooks with tables, your temperature and pressure log files together with the energy consumption data and the energy price forecast can real-time be the fuel to power your AI engine. Data from your own unique refrigeration system.
By feeding a real-time AI engine with data, you can get not only deep analytics about your refrigeration system but you can also create models that you can use to reduce the energy consumption and cut energy costs. You can calculate the savings in different situations, create scenarios without even invest in equipment, and predict system problems.
Remember, the data your refrigeration system creates is a gold mine for your company.
Source: Deep Learning on Medium