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Choosing the Best System for Building Energy Management

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Natalie Patton

Whether you are a building owner or a property manager, the cost of energy waste in commercial buildings is always going to be one of your primary concerns. The U.S. Department of Energy estimates that on average, 30% of the energy used in commercial buildings is wasted, leading to poor building performance. Increased consumption and waste directly impact your operations and maintenance budgets, and you miss out on potential cost-saving opportunities.

One of the most effective ways to optimize energy performance and reduce costs is by integrating a system for building energy management that suits your building’s specific functions. Understanding the role of analytics within such a system can help you choose the best option for your building.   

Creating an Effective System for Building Energy Management

A comprehensive building energy management system provides control and monitoring functions across a range of areas such as HVAC, security, fire alarm, and maintenance. While these systems have substantial benefits, decisions about implementation are often ultimately guided by return on investment (ROI): is it worth it? 

Choosing a system for building energy management with intelligent analytics can optimize ROI by targeting some of the most common sources of waste and helping you to achieve your goals, including:

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.

 

Robust analytics make an effective building energy management system possible, helping you reduce utility and operational costs and resulting in an impressive ROI—now, and in the future.    

Analytics as the Core of Building Energy Management System

The cloud-based onPoint Analytics platform provides multi-layered analytics to ensure your on-premise energy management goals are met. This innovative platform serves as the core of a building energy management system and offers customizable options for setting rules and reporting capabilities specific to your building management needs. By integrating advanced analytics and ML algorithms with user-friendly utility, onPoint can help you create a truly intelligent system for building energy management.

Key features include: 

  • Standardizing tags and naming conventions: If your facility already has proprietary building energy management systems installed, it becomes difficult to aggregate and analyze captured data and improve the efficiency of the building equipment. Through standardized tags and naming conventions, onPoint improves the migration process for upgrades and deployment of new building systems.
  • Streamlining data management: With a cloud-based system, onPoint streamlines and captures historical data of building equipment and transfers data securely to its platform.  
  • Directing maintenance efforts: Through a comprehensive analytics approach that leverages ML, onPoint addresses the issues related to your existing building management system and helps pinpoint the faulty devices that require immediate maintenance.   

With these features, onPoint has been instrumental in accomplishing energy management and conservation goals around the world, including across the sprawling campus of the University of Melbourne

Whether you are responsible for the energy management of a small commercial building or a skyscraper, increasing system management capabilities and reducing costs are critical goals. An advanced analytics-driven building energy management system not only improves the efficiency of the installed systems and maintenance work, but helps you enhance sustainability across your facilities.        

To learn more about how onPoint can help you address building energy management needs, register for our monthly webinars. Or contact our analytics team to get more information about our platform.

 

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