In the simplest cases, rigid upper and lower limits are used to monitor this, and most often meters provide this function. However, this is by no means the best solution, as rigid values do not provide fully accurate information for effective monitoring. There may be fluctuations which they cannot consider. Therefore, a system is needed that can accurately reflect natural load fluctuations.
The key to efficient energy management
Given that energy and resource prices are currently very volatile and rapidly rising, it is natural that most companies are concerned about how to reduce their energy needs. Resource efficiency is a cardinal issue for everyone, so the question arises again and again: where and how can energy demand be further reduced? The key to savings lies in overall transparency of consumption.
To do this, existing databases need to be checked and evaluated to determine which data can be used. Furthermore, in order to calculate the characteristic values, it is necessary to obtain reference values and parameters. The measured data must be continuously evaluated and analysed to ensure that energy management is truly effective.
The energy management module of the CAFM system is a great support in this. This service is able to integrate all the energy consumption data, sensors and smart meters of the facilities into one system. It does this using the latest interface technologies, so there is no data source that the user cannot access.
How does this work in practice?
CAFM’s energy management system aggregates incoming data and displays it in a variety of easy-to-understand formats. It can even be used to create complex reports. This can be a great help and effective support when, for example, you reach a critical point in a decision-making process.
The amount of data that can be displayed simultaneously is limited only by the screen resolution. However, virtual series can be created to reduce the number of data series and increase clarity. All this is facilitated by an easy-to-use interface that allows you to add up data series, calculate averages, and define minimum and maximum values.
All the data in one place
Complex statements, reports
Easy to use interface
Always current, always up to date
Opening new doors in facilities management!
As all the information is completely up to date, this creates another opportunity for facility management. For example, it allows system managers to intervene immediately with error or blocking messages if the values seen deviate from the desired numbers.
We can control systems by means of live diagrams, giving the ideal values. In terms of temperature, for example, you can specify the desired temperature range. As soon as the value falls below or just above it, you will get an immediate message, so you can take immediate action.
Energy management typically takes into account metering and consumption data from consecutive periods. Of these, daily analysis with normal charts becomes too difficult, often impossible – think what happens when, for example, a public holiday comes along. The daily analysis function in Energy Management allows you to compare the values for each public holiday with those for an average period, for example.
Improving the values of the future
For companies with high energy costs, it is essential to have an accurate forecast of future energy and resource needs. Only then can they improve their position vis-à-vis certain suppliers and optimally control consumption processes. How much energy is needed and when can it be bought at a better price? These are perhaps the two most important questions if we want to improve future values.
Specialised tools – trend analysis, forecasts and regression forecasts – can help enormously.
- Trend analysis calculates a linear consumption trend for the future based on past consumption.
- The other option also builds on past consumption, as it creates a forecast model based on it. This is done by normalising the old results by influencing factors. These can always be updated and recalculated if systematic deviations in the results are detected.
- Regression forecasts calculate future consumption based on the influence of basic parameters. These parameters – such as outside temperature, intensity of use, production planning or operating time – are related to the measured energy quantity. The process naturally goes through several periods until it becomes fully stable and reliable enough to predict energy needs.