Features
When applied to historical and real-time data, framework algorithms (formulas) can help you gain insight to better manage your operations. The product includes these features:
- An open and extensible analytical environment that you can customize to meet your needs
- Analytic tools that apply to any industry, including manufacturing, as well as building management
- The ability to set up complex analysis without custom programming
- Support for third-party API visualization and other complementary applications
With these tools you can compare monthly and yearly energy expenditures against targets.
Figure 1. Example of energy analytics
You can scroll through histories to take a look at statistics.
Figure 2. Result of triggering the analytic model
In this example, you can compare your energy for the month to your budget and observe the result. This is evaluating the data in the station by a given time period, every 15 seconds in this example.
The framework can:
- Look for something and let you know it found it.
- Perform a calculation on a set of inputs to give you the result.
- Set up a graphic to visualize data for a particular need.
- Look for faults in systems if you know how a system fails.
The custom rules you create are very powerful.
Often people want to compare a series of histories with a baseline.
Figure 3. Comparison to a baseline
The gray in the background shows last year’s monthly performance compared to this year’s blue bars.
Algorithms designed to work with a specific data type, such as electrical consumption (KWH), could easily be duplicated and modified to instead work with water consumption (gallons) or gas consumption (ccf). This is possible because inputs to algorithms are defined based on tags, such as hs:energy to identify a source of electrical consumption instead of being bound to specific control points (end points) in the station.