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Artificial intelligence, genuine results

Utilities represent a significant portion of a building’s operating budget – typically 30% to 40%. Electricity and gas are primarily consumed by the building’s heating, ventilation and air conditioning equipment, and the amount of waste involved (defined as the supply of energy exceeding demand) tends to be significant.

Innovation has been slow to come to HVAC management. Many of today’s multi-family buildings manage their HVAC energy consumption the same way they did 20 years ago. The process is not data-driven, dynamic or measured against historical patterns, and it certainly isn’t forward-looking. If anything, it continues to reinforce an unnecessary pattern of waste.

But thanks to technical advances in how buildings use data to measure demand, control and supply of energy, owners and operators of multi-family properties now have numerous opportunities to lower their operating costs and increase the value of their assets.

The prospects
Advances in artificial intelligence and the Internet of Things present the opportunity to transform and eliminate energy waste in buildings. AI is evolving rapidly, and the accessibility of best-in-class data processing techniques and infrastructure means small teams can deliver big results. When AI is applied to a building’s operational data, the software can extract information and learn how the HVAC equipment should operate to minimize waste. The continual collection of real-time data and automated trend analysis drive ongoing and incremental performance improvement.

Similarly, advances in IoT performance and lower costs make it possible to cost-efficiently build (and program) a network of sensors and controllers that can serve as an HVAC monitoring and control system. A large multi-family building might require 100-plus data sensors and controllers, which can be purchased for a minimal upfront investment. Successfully implemented projects can yield very high returns on investment.

With respect to data infrastructure, today’s broadband networks can transport thousands of data points per second to the cloud for AI processing. This technical landscape makes it possible to transform an analog building environment that relies on manual data logging, trend analysis and equipment scheduling into a real-time control system that is digital and seamless, allowing buildings to become fully connected and data-driven.

The process
Every building is different. To develop a cloud-based energy management solution, the first step is always to have a qualified professional, ideally a Certified Energy Manager, perform a walk-through assessment. During an assessment, it’s critical to inventory all of the existing HVAC equipment, how it is (or isn’t) being controlled, and potential data points and historical usage patterns for both electricity and gas, determined through utility bill analysis.

This information can be used to generate a new building profile – the baseline energy performance and potential building performance – driven by a cloud-based, AI-driven energy management platform. The assessment will identify any capital upgrades required (sensors, variable-frequency drives, relays, tie-ins, metering, programmable logic controllers, cellular communication) to ensure that all of the required data points are available in the cloud for the software to run effectively.

With these capital costs, software costs and targeted energy savings in mind, the business case can be presented to decision-makers. In our experience, simple payback for multi-family projects typically ranges from one to three years, depending on the size of existing equipment and level of automation currently implemented.  

Once a business case is established and a project moves to implementation, all of the required sensors and controls will be installed and tied into the building. Through a monitoring period, data is collected, aggregated and parsed as needed to build an accurate profile of the building’s operating characteristics. Once process-level baselines are accurately established and it’s confirmed that the energy management platform is receiving all of the needed data points for the software to run, the building transitions into full automated control. 

During operation, the energy management platform should provide access to building data, including actual performance relative to the baseline, as well as data insights on the operation of equipment, including fault detection and performance anomalies. The newly available equipment and process-level data can assist the building operator in managing issues before they become headaches – for instance, alerts to equipment failures that could put tenant comfort at risk.

From a financial perspective, energy management platforms help to increase asset value. Owners can experience short-term payback on their investment through operational savings that begin as soon as the platform starts controlling equipment. Equipment costs can also be financed over extended periods to ensure that projects remain cash flow positive from day one. Over time, energy management lowers expenses and increases both net operating income and the overall property value.

For these reasons, property owners and real estate investors can benefit from implementing energy management platforms in their buildings. The opportunity to eliminate energy waste is compelling from a financial perspective and comes with the added benefits of providing data insight on building operations and improving the service offered to tenants. The time to consider a cloud-based, AI-driven energy management platform is now.

Artificial intelligence, genuine resultsMike Mulqueen is vice-president of business development for Parity, where he’s responsible for building strategic partnerships with portfolio managers, property management companies, mechanical contractors and other like-minded businesses. Previously, he led energy conservation strategy and key account customer engagement for the commercial and multi-unit residential sectors at Toronto Hydro. For more information, visit paritygo.com.

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