
Load control Proof of Concept project at a hospital in Suncheon, Korea
From data to energy savings: how a hospital can achieve 7% energy cost reduction with AI-powered Self-Demand Response technology.
Company profile
Industry: Healthcare
Facility: 9-floor hospital
Energy profile: 300 AC units | 5 MW capacity
Air conditioning cost: USD 10,000 / month
Location: South Korea
The challenge
Rising energy bills driven by inefficient operation of air conditioning systems
Lack of visibility into real-time energy consumption patterns
Limited insight into what distributed energy resource could support cost reduction or peak demand management
No optimization of energy use across floors, zones, or different times of day
No data-driven decision-making tools to guide efficiency improvements
The solution: xVPP Powersight
xVPP Powersight is an advanced energy data analysis platform that provides granular monitoring, trend and cost analysis, energy resource simulation, abnormal peak detection, and AI-powered insights and recommendations.
The analysis:
AC setpoints and cooling performance
Thermal comfort based cooling setpoint
AC operation patterns per hospital floor, zone, and facility type (time of use and peak load timing and sizes)
AC operation mode
The results
Air conditioning energy usage is expected to decrease by about 9%, resulting in roughly 10% savings in air conditioning costs
Expanding load management to additional buildings in the hospital complex could yield approximately 7% energy savings on monthly bills
The overall monthly savings potential increases to up to 19% with maximum demand reduction
In a simulated scenario that includes load management and the integration of solar PV and battery ESS resources, the hospital could achieve monthly savings of up to USD 20,000 (equivalent to approximately 15–20% of its total electricity bill).
7%
estimated total cost savings potential
10%
cooling costs saved
19%
cooling costs saved incl. maximum demand reduction
$20,000
monthly savings simulated under solar & battery resource adoption scenario