DataModeling_EnergyManagement_graphic

Data Modeling in the Context of Energy Management

Data models are available in many database applications and the purpose is generally the same, but the DataEye Pro™ data model is a step above most. Here, I’ll explain how the DataEye Pro™ data model functions in the case of Energy Management Systems (EMS).

The goal of DataEye Pro™ when applied to EMS is to perform analytics, or formulas, on common mechanical system equipment, energy meters, lighting controls, and other intelligent systems within a building. The key benefit to running formulas against a data model in this case – as opposed to running a data model on each piece of equipment individually – is the ability to manage updates and consistency across a building or portfolio of buildings for an accurate read on current system performance.

Data Normalization vs. Data Modeling

Niagara AX™ does a fantastic job of normalizing data. Tridium and its developer partners have amassed an amazing amount of drivers for legacy control systems and open communication protocols to bring data together in a truly revolutionary way for the energy management market. DataEye Pro™ takes full advantage of this normalization and then adds another layer of complexity to the data – context. For example, in the DataEye Pro™ model, a rooftop air conditioning unit is a rooftop unit regardless of the manufacturer, communication protocol, or controller manufacturer; a lighting circuit is a lighting circuit regardless of the technology in the lighting fixture or lighting control panel. With this baseline understanding, the information in the database is modeled through DataEye Pro™ in a way that is exponentially more useful.

Consider this scenario: One popular sequence for controlling chiller plants today is to reset the chilled water supply temperature based on demand from the building (these buildings can be commercial office buildings, industrial process plants, data centers, or any other type of environment requiring cooling). The data sequences for this strategy can include complex strategies or ones that are fairly basic, but the challenge is to attain similar success rates in multiple applications of the same sequence. DataEye Pro™ enables just this sort of repeatability, with Responsive Analytics™ that pull real-time data from all building systems by writing back to the building’s control systems (a feature enabled by Niagara AX™’s data normalization capabilities). In this instance, the data model can be built one time for use across several chiller plants, with different control systems, and across multiple chiller manufacturers. Required variables and optional variables can be built into the same strategy to enable truly repeatable results across multiple buildings simultaneously. These applications can be executed from the cloud or locally in the buildings, allowing for true scalability (thanks to the improvements in server and cloud technology in the last several years).

Since Niagara AX™ also includes a powerful historical database, it is possible to use this information set to gain an understanding of how the system has performed in the past. When the historical data is available in the context of real-time data, sequences become predictive in nature, controlling to set-points established by historical performance to allow for more accurate decision making.

Just as weather forecast data is used to predict energy consumption by several products today, this same information is combined with a building’s real-time information to predict power demand curves, energy profiles, and costs. But prediction is not enough. The real-time control strategies then use this information to further improve the overall energy efficiency of buildings.

Though these are a couple applications enabled by modeling the data in Niagara AX™, there are many more applications where DataEye Pro™ can be utilized in the context of energy management. The targeted methods employed by DataEye Pro™ are specifically designed to run analytic formulas in a near real-time environment, taking advantage of ancestral relationships and meta-data to impact only the appropriate pieces of the data model for all the energy management needs of any building or portfolio of buildings.

To learn more about how DataEye Pro™ can help with your energy management or other specific applications, contact us

Leave a Reply

Fill in your details below or click an icon to log in:

WordPress.com Logo

You are commenting using your WordPress.com account. Log Out / Change )

Twitter picture

You are commenting using your Twitter account. Log Out / Change )

Facebook photo

You are commenting using your Facebook account. Log Out / Change )

Google+ photo

You are commenting using your Google+ account. Log Out / Change )

Connecting to %s