Recent studies conducted in South Korea and Hong Kong reveal that current energy efficiency measures for buildings are not sustainable. AI experts provide a solution with a 10x faster payback period than building renovation.

As cities strive to meet carbon neutrality goals by 2050, energy efficiency in high-density urban centers located in Asia has become critical. Recent studies conducted in Hong Kong and South Korea highlight major challenges, ranging from regulatory to financial issues.

“High-density urban centers are at the forefront of sustainability and our fight against climate change, yet they face significant hurdles in achieving energy efficiency. We need to put more focus on energy performance management in Asia if we want to reach net-zero goals in as little as 30 years,” said Donatas Karčiauskas, CEO of Exergio, a company that provides AI-based solutions for energy management in commercial buildings.

A comprehensive analysis of 36 office building retrofits in Hong Kong identified 23 major challenges, including inadequate government incentives and long payback periods. Regulatory hurdles emerged as the primary barriers, followed closely by financial concerns.

In South Korea, the effectiveness of the Building Energy Efficiency Certification (BEEC) system has been questioned. The study indicates that current certification levels might not reflect true energy efficiency, revealing significant energy consumption discrepancies in office buildings and educational facilities.

“When traditional retrofitting is not feasible, AI-based energy performance tools offer a viable alternative,” stated Karčiauskas. “First of all, AI-driven platforms are easier to implement and their payback periods are up to 10 times faster, on average 2 years instead of 10. AI energy performance tools also provide real-time data and actionable insights to reduce energy consumption and emissions.”

In previous projects conducted in various countries across Europe, Exergio’s AI platform reduced energy waste by up to 20% in office buildings.

These numbers are achieved by aggregating data from various sensors and meters, and performing cross-checks and technical analyses to provide actionable insights. Advanced AI algorithms not only monitor but also optimize building operations dynamically, enabling immediate adjustments based on current conditions.

“The main challenges in managing heat, cooling, and building systems stem from the dynamic nature of internal and external conditions,” Karčiauskas explained. “AI tools can continuously analyze these changing conditions and predict optimal settings, ensuring systems operate efficiently without manual intervention.”

AI can adjust heating and cooling systems based on real-time data, such as reducing cooling in unoccupied areas and ramping it up before peak usage times. This real-time adjustment capability helps maintain comfort while reducing energy consumption.

“While AI significantly enhances automation and can perform many tasks faster and more accurately than humans, human oversight remains crucial,” added Karčiauskas. “AI can help identify potential issues in HVAC systems and suggest solutions, but human technicians are needed to verify and implement these solutions. There is a huge potential in such AI-based technologies in Asia, but a leading city in energy efficiency is yet to emerge.”