Choosing the Best System for Building Energy Management

Increasing Equipment Uptime 

Problem: In a commercial building, a system failure or a maintenance issue can lead to significant equipment downtime and quickly run up costs. 

Solution: A smart building energy management system monitors the operation of an interconnected network of equipment and devices continuously and can immediately detect when something is out of whack. This means faults are quickly identified, isolated, and addressed to minimize downtime. 

Reducing Maintenance Costs

Problem: Interval-based maintenance of building equipment is often unnecessary and inefficient. Not only do unwarranted maintenance visits add to costs, this reactive approach leaves the system vulnerable to human error, is highly dependent on manual intervention, and can increase the need for expensive emergency repairs.

Solution: An intelligent analytics platform with advanced fault detection and diagnostics allows you to take a proactive approach to maintenance while ultimately minimizing the need for manual intervention over time. 

A building energy management system using advanced machine learning (ML) algorithms offers predictive analytics that identifies equipment and system failure in advance by comparing the operational performance data of building equipment to its historical data. Timely and relevant alarms triggered by the system according to point-level fault detection rules notify you of compromised performance according to a range of variables, including energy consumption, faults, and run-time, rather than simple change of value metrics prescribed by the design engineer years before the building was actually operational. Furthermore, advanced analytics can correlate the conditions of the building with the functioning of the equipment network, consolidate multiple alarms, rapidly identify the likely causes of malfunctions, and make targeted recommendations for corrective action. 

Not only does this approach minimize false alarms, it drastically reduces reliance on human intervention to identify and address operational problems. Analytics with an ML-based approach also opens the door to additional advanced capabilities, such as historical data and anomaly detection-based triggering of adjustments to operational setpoints and initiation of automated actions that modify building systems configuration and behavior. 

In the long-term, this proactive approach can improve the useful life of your building automation system and extend the lifespan of a range of building equipment.

Predicting Operational Costs

Problem: Without the ability to predict operational costs, it can be difficult to create and evaluate strategies that improve efficiency.

Solution:  A building energy management system using machine learning algorithms, based on tracking and modeling a range of historical data, forecasts future data trends on energy consumption and the resulting operational costs. These predictions can be used to uncover opportunities to reduce costs and emissions through smart, efficient, and streamlined energy management.

Improving Access to Data

Problem: As a property owner or a facility manager, data on energy consumption, equipment monitoring, and maintenance is essential to understanding how a building functions and analyzing the costs and the scope for savings in building operations. But building systems produce massive amounts of data, often obscuring rather than illuminating critical insights.

Solution: A user-friendly building energy management system can provide prioritized data, actionable insights, customizable reports, and represent data through an interactive dashboard in a way that makes sense for you and other stakeholders. In other words, it makes data accessible, visible, and meaningful.

Enhancing Comfort

Problem: When it comes to increasing the appeal of your building to prospective and current tenants, comfort is a top priority. This includes ensuring proper functioning of equipment and timely resolution of maintenance requests. The limitations of traditional systems can make this difficult due to reliance on manual intervention and reactive maintenance.

Solution: By automating critical building systems and addressing maintenance issues before they are noticed by occupants, an advanced system for building energy management can help you improve occupant comfort. Additionally, these systems allow you to produce more accurate invoices for utility usage, increasing transparency.