Are AI and IoT far off concepts? No. They exist now and produce measurable energy savings. I trust you care about increasing energy efficiency in your building. If so, then you’ll want to see some of the options available today.
You’ve probably heard about the benefits of LED lighting. You may have even replaced your old incandescent bulbs with LED bulbs. LED lighting retrofits represent the low-hanging fruit of energy efficiency because of their low cost. No major changes to the building are required.
With that done, what’s next? You know the decisions get much more difficult to establish an energy efficiency plan. Let’s get practical and delve into common challenges facing buildings.
The Problem with Buildings
Most building owners and operators believe that a Building Management System (BMS) solves their energy efficiency problems. Not true, unfortunately.
A BMS was not designed specifically for energy efficiency. They run the major mechanical, electrical and plumbing systems in a building. Unfortunately, a BMS typically operates non-optimally. Even a newly installed BMS cannot guarantee optimal energy efficiency.
You could choose to modify a BMS by adding additional data points and altering the control software. Unfortunately, BMS system modifications are expensive.
To some degree, buildings that do not have a BMS face an easier road to energy efficiency. They offer a clean slate by which AI and IoT retrofits can quickly realize energy savings, all for a fraction of the cost.
Many buildings already capture real-time data from the main electrical meter. This helps with real-time visibility because only the monthly electric bill was available previously.
The problem, however, is that the main electrical meter does not provide any insight into the actual sources of consumption. Was the high energy usage related to a particular tenant? Was the spike in energy consumption due to a failing HVAC system? Regardless, the main meter data does not provide insights to the actual source of inefficiency.
You must go beyond the main meter. Remote sub-metering provides electricity consumption information on a circuit level. For example, you can install electrical sub-meters at remote parts of your building to determine the consumption of individual circuits. Modern sub-meters (see examples) can capture real-time data (e.g., voltage, current, kWh, etc.) from 48 single-phase or 16 three-phase circuits using a single IoT device. Imagine the ease of wirelessly transmitting all of the sub-meter data to the cloud for real-time dashboards. IoT opens up a range of possibilities in sub-metering.
Great benefits await those that capture remote sub-meter data at the circuit level. IoT devices enable the generation of a granular mapping of energy consumption by each monitored circuit. AI can then perform a circuit-level analysis to determine when consumption varies from an established baseline.
Critical Building Asset Monitoring
A BMS controls critical building assets such as cooling towers, chillers, RTUs, etc. Unfortunately, the BMS will not necessarily capture granular details of operation. A key question remains. Have the critical building assets been operating efficiently? IoT devices can capture detailed data such as supply/return temperatures, compressor run times, power consumption, and vibration. This granular sensor data provides keen operational insights.
Automated Intelligent Controls
A BMS is not typically optimized for energy efficiency. Limited availability of sensor data represents one of the main culprits. For example, a BMS may not have the benefit of occupancy data from the building, an array of temperature/humidity sensors scattered throughout a particular zone, peak demand program alerts, etc.
IoT solves this data problem. Retrofit IoT sensors capture additional data relevant to the HVAC controls. This IoT data would supplement existing data extracted from the BAS itself using industry standard protocols such as BACnet.
The cloud aggregates the IoT data and BMS data into Big Data. An AI Analytics Engine would then process the Big Data to produce automated intelligent controls. AI optimizations would then be fed back to the legacy BMS to supersede the HVAC programming.
The cloud would transmit HVAC commands (e.g., changing of temperature setpoints) to the on-site BMS for execution. This architecture implements a type of virtual BMS that treats the on-site BMS as a sub-system. Any higher-order intelligence implemented in the cloud would override the on-site BMS. This overlay of intelligence on top of the BMS will generate huge savings into the future.
For buildings or tenant spaces (e.g., retail) that do not have a BMS, remote thermostat controls provide a great opportunity for energy savings. Remote management of temperature setpoints ensures that evening, weekend, or holiday time periods can realize energy savings. An automated energy efficiency program cannot rely on manual execution by employees.
IoT solutions today can integrate with stand-alone thermostats to provide remote management of temperature setpoints. The cloud can establish thermostat schedules remotely. Wireless commands sent from the cloud make remote thermostat management simple. Large energy savings result. AI and IoT can enable a virtual BMS that shifts the intelligence of a thermostat into the cloud. Unobtrusive installation and minimal installation costs already produce outsized ROI. It’s available now.
AI and IoT Can Save Energy Today
AI and IoT deliver practical energy-saving solutions today. Take advantage of them at a fraction of the cost of modifying an existing BMS. If your building does not have a BMS, you have an even easier choice. Retrofit solutions deliver smart building functionality where none exist. Savings will inevitably follow.