Improving building energy performance

Commercial property is in a particularly tough place these days - not only is it suffering as a whole from the downturn in the economy, but radical changes are being asked of the industry in how it develops and manages property and how it measures success. Among those requested changes are calls for more energy efficiency, given that commercial buildings typically consume 40+% of Australia’s energy output, which emits significant volumes of CO₂.

With the increased focus on energy performance, the building industry is being asked to deliver more, despite the downturn, meaning less capital and fewer resources than ever. Building systems must be more energy efficient and less costly (or in the worst case, no more than their less energy-efficient equivalents). For retrofits, payback requirements have tightened as capital constraints are even greater.

Traditional building management

The challenge with managing a building’s energy performance is that most of today’s building owners have to address two apparently conflicting goals: firstly, to make tenants as comfortable as possible so that productivity is maximised and leases are maintained and renewed. Secondly, to meet or (as in today’s downturn) reduce the energy cost budget. Traditionally, more comfort has generally equated to higher utility costs. And now in our energy performance-oriented world where energy ratings such as NABERS in Australia exist, a third goal is introduced for building owners and managers - reducing emissions.

Proactively achieving these three competing goals in a complex commercial building environment becomes almost impossible with today’s conventional building management system (BMS) tools. Despite high levels of control at the subsystem level (eg, air temperatures and flows), there is limited global control and direction across the whole building, nor is there awareness within the BMS of other factors which greatly impact on costs and emissions, such as weather forecasts or utility rates.

Consequently, the burden and requirements of these challenges have fallen to building managers - a tough ask given the complexity of most buildings and their energy systems. To add to this, with the downturn in the industry, resources have been cut, so there are fewer managers in buildings and, in fact, the best building managers are being pulled up a level to manage a portfolio of buildings, putting less-expensive, lower-skilled managers on the ground to make difficult day-to-day decisions.

Proactive energy management

In the face of these challenges, new technology is emerging that addresses these problems and promises to redefine the way energy is managed in buildings. The technology helps owners reduce energy costs without impacting tenant satisfaction; it also aids building managers to proactively manage energy, while freeing up their time to focus on other important tasks. Best of all, the technology is delivered in software, which means lower costs and shorter payback cycles.

One of the most advanced classes of this technology is predictive energy optimisation (PEO) software, sometimes referred to as an ‘autopilot system’ for building energy management.

In an airplane, the autopilot system understands the plane’s internal operations: engine performance and specifications; flap and rudder responses to changes in controls; fuel capacity and consumption under different conditions; and cargo and passenger loads. It must also consider numerous external factors: distance and direction to destination; existing and forecast weather; winds; and air traffic. Considering all of the variables, it then calculates the optimal flight plan to the destination. This is preset before take-off, but after departure, the flight plan is continuously re-optimised, based on any changes in conditions. Ultimately the autopilot guides the plane along the most efficient, optimal route given the various constraints.

PEO works the same way - it understands the internal and external conditions of the building, and then guides the energy systems to the most optimal use of energy to achieve its goals. This software overlays the BMS and optimises energy use by continually changing BMS setpoints when required.

In terms of internal conditions, the software considers several aspects of the building: thermal characteristics of the building; mechanical plant operations and capacity; existing BMS settings and tenant occupant times; and load variations.

The software ‘learns’ the internal operations, creating a complex energy model which enables accurate forecasting of energy requirements under different conditions. It also considers important external conditions such as weather and weather forecasts, the building’s energy prices and tariff structure and utility grid information and events, such as demand-response (DR) events.

Given the building’s energy model and the external factors, the software determines the optimal plan for the building, targeting the best balance between the three competing goals - energy cost, consumption and occupant comfort. Much like the airplane, the plan is set a day ahead, but is then continuously re-optimised, based on any changes to conditions.

Figure 1 demonstrates how PEO works on the HVAC systems in a typical building during a typical day (real data from an existing building where a PEO system is deployed is shown). The blue line shows the power levels from the existing settings on the BMS - starting every day at the same time to ensure the right conditions at occupancy, running at similar power levels all day to maintain target temperatures, and shutting off at the day’s end. In contrast, the red line shows the power levels which result from PEO and tailored to the specific day’s weather and the utility rate structure in place. Morning start-up is optimised to take advantage of low overnight temperatures and the building’s thermal mass to store energy, still achieving the right conditions at occupancy but using much less power than the standard settings. Power levels are increased as the day warms and, later in the afternoon, the system ramps power further to pre-cool the building prior to the peak electricity rate period which starts at 2 pm (this approach is used to automate the response to DR events to decrease loads during days where the grid is strained). After rate changeover, pre-cooling allows the building to ‘drift’ on much lower power levels, with gradual changes to maintain comfortable conditions the rest of the day.

Figure 1: Comparison between conventional and predictive energy optimisation energy load.

Deploying predictive energy optimisation

This software can be used with many of types BMS and HVAC infrastructures in commercial buildings. No upgrades to the building or new sensors are required, although some minor sub-metering and an internet connection are needed. Installation and tuning of the system is heavily automated, with most of the configuration work done remotely after the initial install. Importantly, the software can be installed without disrupting existing building operations.

PEO software can be deployed in new building construction or retrofits. It makes some sense to install PEO during a BMS upgrade, to coordinate programming works; however it can be installed in operating buildings that have no upgrades underway as well.

Many of these PEO products are bringing software business models to the building industry, charging subscription fees rather than upfront costs and requiring no capital outlay to install and get started. As a result, the system should pay for itself starting within months of being deployed.

Results and benefits

PEO software can save as much as 40-50% in HVAC energy on a given day with the right conditions, and 20-30% on a continuous basis is not uncommon. This improvement can translate into a 5-10 point Energy Star increase, and could mean the difference between getting an Energy Star Label certification, or not. This may result in even greater financial benefits given the significant reduction on peak tariff energy use. In addition to the financial benefit, the system will dramatically reduce the time required to manage energy in the building, thereby freeing up building operations staff to focus on other tasks.

In response to the increasing market and regulatory pressures and operational complexities, new solutions such as PEO software are being created to help reduce emissions, costs and operational complexity in buildings.