The Interplay of Digital Twins and AI: Revolutionizing Energy Management and Optimization

Energy industry professionals face the continual challenges of optimizing power usage and management at a time when many modern activities increasingly strain the existing infrastructure. Many have explored how to use artificial intelligence and digital twins to support their efforts. 

These technologies have historically served different purposes. Whereas a digital twin represents a highly detailed model of a real-life asset, AI fulfills a broader function, such as assisting with data analysis, predictive maintenance and performance optimization. However, some companies now combine the two technologies into single products. 

Whether people use digital twins and AI together or separately, how can these innovations improve the world’s energy use while increasing grid stability?

Succeeding With Digital Twin Applications in Energy Decarbonization Strategies

Electric company executives, property managers and budget-conscious consumers are among the many groups interested in making buildings more energy-efficient for the long term. Relatedly, many city planners and other decision-makers realize they must strategically decarbonize the structures under their influence. How can they decide which ones to target first through remodels and other upgrades? 

Professors working in New York believe their detailed digital twin could hold valuable clues. It shows the carbon emissions and energy consumption of each building in Ithaca. Many similar products only assess individual buildings, but this one groups them. This allows several building owners to examine the effects of collaborating and purchase one energy-efficient upgrade that would benefit them all. 

This digital twin presents users with thousands of possibilities based on building type, clustering similar ones. Additionally, the compiled information about the city’s structures allows people to analyze how specific wall materials or foundations impact energy efficiency. They can also examine geometric particulars to gauge a building’s suitability for solar panels.

How might the digital twin’s information support energy-efficiency AI gains? Construction managers and others overseeing building upgrades could initially use the digital twin to determine the most likely results from particular enhancements. Building occupants and other concerned parties could use artificial intelligence algorithms to track how close real-life usage is to what was predicted. 

Deploying Utility AI Solutions for Better Stability

Electricity operators must keep the grid performing well despite frequent fluctuations caused by energy-intensive applications. Digital twins can aid their plans by revealing the likely effects of particular situations, showing executives existing infrastructural weaknesses or potential threats. 

Eventually, many decision-makers may also use AI in energy management to reduce spikes that could make the grid more vulnerable to blackouts. In one example, researchers developed artificial intelligence algorithms that detect conditions adversely affecting the grid’s voltage balance and automatically respond to stabilize operations. 

The group noted that supply and demand variations caused by newer technologies — such as electric cars and renewable energy — make it more difficult for the grid to maintain steady voltage. This innovation takes a decentralized approach to energy management. The researchers believed it would be more efficient and cost-effective than centralized solutions. They also demonstrated it in the real world within smart microgrid hardware. The results indicated this AI application could maintain voltage levels within certain parameters, increasing the grid’s stability and reducing the likelihood of infrastructure damage. 

Ongoing maintenance is also essential to a smoothly functioning grid. Using AI and digital twins for predictive maintenance in utilities is an increasingly accessible option, especially because it can help managers determine the number of technicians required to cover specific areas or infrastructure. Additionally, many AI algorithms can detect abnormal symptoms that are too minor for humans to notice. Knowing about those issues sooner better equips maintenance specialists to diagnose and address problems before instability occurs. 

One digital twin solution for an Australian energy facility enabled technicians to spend 75% less time at physical locations because they could do virtual checks first. This is a strong example of how technology can augment rather than replace industry employees.

Applying Technologies for Improved Planning and Resilience

Better visibility is an often-mentioned benefit of digital twin software for energy companies. Many cities are increasing their renewable power deployments or electric vehicle charging stations, potentially straining existing electricity infrastructure. Additionally, as many areas of the world experience severe housing shortages, numerous developers have acted to curb it.

A smart grid digital twin or AI-powered energy optimization tool could support planning committees, local utility companies and other parties as they envision new communities. An example from Germany will accommodate 7,000 residents within approximately 188 acres in the nation’s capital. Those bringing this vision to life will use digital twins, AI and other advanced technologies to ensure the community is highly livable and thoughtfully designed for the future.

An energy-specific digital twin forecasts power usage, while a building-centered one helps people determine the best ways to work within the existing area and its infrastructure. These tools also optimize energy efficiency, giving people the information needed to construct new buildings or upgrade those currently there.

A wastewater heat exchanger and heat pumps will provide the community with 100% carbon-neutral heating and cooling in 2026. Digital twins and AI algorithms could assist project managers with setting performance goals. Statistics also indicate that sustainable buildings have up to 21% higher market values than their counterparts. Professionals who approve such projects now could reap the rewards during occupancy due to lower bills, as well as when they eventually try to sell those properties. 

Visitors and other stakeholders can also use the digital twin to tour the planned community virtually. They will enter a showroom and be able to experience the planned community, even though construction on the physical version has only recently begun. 

Promising AI and Digital Twin Applications in Energy

Decision-makers can anticipate benefits including better visibility, improved resilience, and cost savings from AI and digital twins in energy management. They are most likely to optimize outcomes when considering their most pressing needs and how these technologies could address them. 

However, there are also challenges of using AI and digital twins in the utility sector. Many stem from people’s initial unwillingness to change, especially if they believe the current ways are sufficient. Moreover, if a utility plant primarily has legacy equipment, it may be more challenging than anticipated to make newer technologies work with it. Keeping an open mind and exploring creative solutions for overcoming obstacles will reduce their effects.