How data can enable sustainable retrofit

Although there is an increasing demand for net-zero buildings, retrofitting older, less sustainable assets can actually save 50–75% of the embodied carbon associated with new construction.

The way to improve such existing buildings is twofold: first, to find a means of reducing the overall energy consumption and, second, to replace fossil fuels with renewable sources. Data is key to both of these, and smart technology can be used to transform energy distribution systems and monitor building operations.

Analysis of data from the IoT sensors can provide insights on usage patterns and identify where most of the energy is being expended. Combined with analytics, this data can be used to detect poorly optimised equipment that results in high energy use. It can prescribe equipment maintenance, repair or replacement, to reduce load and optimise consumption by sending out timely system alerts to the facilities management team.

Artificial Intelligence (AI) platforms can automatically control the environment and operations inside and around the building. These include occupancy sensors for optimal movement and space utilisation as well as sensors that allow control of lighting, temperature and air quality. Data from such sensors can serve as input for AI algorithms that further improve automation and efficiency.

The IoT can also provide the interconnectivity that enables various components to talk to each other, automating energy-efficient decisions as shown, for example, in Figure 1. An interoperable building is the first stage in creating an energy-friendly environment. This gives assets owners more control over energy consumption and costs, helping them meet sustainability goals.

Owners of older assets can fit these energy-gorging systems with economisers, allowing them to better observe their use and improve efficiency. Economisers include logic controllers and smart sensors that draw in outdoor air to reduce the operational time for the HVAC compressor. 

HVAC systems can also be upgraded by integrating variable-speed drivers into smart control software. This allows owners to run them at lower speeds according to demand, so they can make energy savings of 10–15%.

Such smart control software runs on the building management system (BMS), which helps regulate electrical and mechanical equipment.

It can help owners exercise control over every programmable and interoperable unit from power, lighting, plumbing and HVAC to solar thermal units, fire alarms, video surveillance and access control. The system itself can be configured across several devices, whether condition monitoring or predictive maintenance using sensors.

Pairing motorised electro-mechanical systems such as HVAC, and operable vents and windows, with a range of IoT equipment enables occupants to improve the comfort of their internal environment, by adjusting temperature and humidity. The BMS can alert owners to upcoming maintenance needs or predict device malfunctions through the BMS dashboard.

The BMS web dashboard is a centralised interface between the integrated building systems and the owners. It uses intelligent software tools to analyse and display insights from sensor data. Building owners can use the dashboard to better comprehend building energy usage, make changes as needed, and address concerns from performance abnormalities.

With a combination of BMS and IoT run over 5G networks, building owners can use strategic insights to inform efficient energy management from a centralised dashboard.

Intelligent controls and smart energy grids can help such buildings export the excess power they generate to the grid. This not only helps owners with carbon credits, it also establishes a distributed energy generation model. Buildings can produce energy that can be redistributed through the smart power grid to other consumers, making for even greater sustainability.

This technology uses AI algorithms that draw context-specific insights from the data to auto-adjust building conditions for optimal function. The digital twin accurately predicts energy performance by using simulations, and enables sustainable operational enhancements to control energy savings and support occupant health.

To understand what a given building needs, so-called fit-gap analysis can be used to identify suitable measures. Meanwhile, a high smart readiness indicator score can determine what's best for each retrofit project. 

Using insights derived from data is the first stage. To achieve the triple ambition of sustainability, energy-efficiency improvements and green economic growth, we have to build the path brick by byte.