A case study from Helsinki: Seeking sustainable solutions using digital twins

In the Art of Taking Action, author Gregg Krech wrote, “We are all depending on each other, as we weave our lives, families and communities together. So, when we do not carry our weight, the fabric gets a buckle in it.  I’d like to think that designing, building, and operating infrastructure plays a significant role in weaving our lives, families, and communities together, as Krech said. And with that, we carry the weight of advancing that infrastructure for a more sustainable, environmentally friendly existence.  As climate change continues tothrow the world of balance, numbers show it is the designers, builders, and owner-operators of infrastructure who will need to lead the transition to low carbon solutions, waste reduction, and energy conservation.

According to the UNOPS report Infrastructure for Climate Action, infrastructure “is responsible for 79 per cent of total greenhouse gas emissions and 88 per cent of all adaptation costs”.Clearly, no one can tackle these sustainability challenges alone. So, how do we work together in the quest to meet and exceed sustainability goals while we design, build, operate, and maintain the world’s infrastructure?

Empowering action for sustainable development

In 2015, all UN member states adopted the 2030 Agenda for Sustainable Development with 17 sustainable development goals (SDGs) for humanity and the planet.

Using an infrastructure lens, we can zoom in on one goal to empower organisations in their effort to design, build, operate, and maintain infrastructure sustainably: Goal #17, to “strengthen the means of implementation and revitalise the global partnership for sustainable development”.

Empowering effective implementation and collaboration through partnerships requires a data-centric approach. Most data, while abundant, is typically siloed in different formats, multiple repositories, and various disciplines across the supply chains.

Using a data-centric approach removes these boundaries and provides open access to extract value for problem-solving.

Likewise, digital twins enable organisations to visualise and analyse data to make more informed decisions. This decision intelligence has been proven to reduce waste and lower carbon emissions in the construction and operation of infrastructure, and even conserve energy and water.

From decision intelligence to sustainable solutions

In Finland, for example, the smart city of Helsinki uses natural gas to power its central heating system.

Transmitting heat from a central source through a network of insulated pipes, these systems work to warm individual buildings. However, even with regular care, those heating and water systems deteriorate with age, leading to leakage events that can cause service outages, energy inefficiencies and water insecurity.

Action #1: Optimise data and expertise

Using a data-centric approach, Suur-Savon Sähkö Oy, one of the largest grid operators in Finland, partnered with an artificial intelligence (AI) laboratory to develop a data-driven asset optimisation service for the citywide pipe networks. They unified data from numerous systems into a single view of overall pipeline health.

Action #2: Let digital twins and AI do the work

These two organisations leaned heavily on digital twins and AI to develop a federated source of pipeline network data that owner-operators could use to improve operations and eliminate water leakages. The AI laboratory brought together all data, including information on heating and water supply, as well as detailed data on pipeline age, type, and condition.

They then developed a method to analyse the data and visualise it in an intuitive user interface, leveraging an open, collaborative digital twin platform. The AI-driven cooling performance analysis significantly improved energy efficiency and decreased fuel consumption, lowering the heating network temperature by 3 degrees Celsius.

By determining how to prioritise maintenance activities where leaks are likely to occur, the pipeline owner-operator also restricts water loss and prevents blockages and outages while reducing maintenance costs.

Action #3: Reuse and recycle

For most practical purposes, any data can be federated into a single digital twin, which becomes a kind of centralised data repository (connected data environment) open to all and easily consumed in its native format.

Resolving Helsinki’s central heating system challenges started with a data-centric approach, weaving artificial intelligence and digital twin technology into its infrastructure operations to bring energy savings and water security to its citizens.

An open, accessible digital twin platform where the disparate data is federated in one place empowers third-party companies and their customers to achieve sustainable development goals for infrastructure. This is a true example of the collaborative ecosystem needed to accelerate the Global Goals implementation, and one of many implementations effectively changing how we design, build, and operate infrastructure to reduce our impact on the planet.